AI tagged posts

AI Draws Most Accurate Map of Star Birthplaces in the Galaxy

Osaka Metropolitan University scientists identified about 140,000 molecular clouds in the Milky Way Galaxy from large-scale data of carbon monoxide molecules, observed in detail by the Nobeyama 45-m radio telescope. Using AI, the researchers estimated the distance of each of these molecular clouds to determine their size and mass, successfully mapping the distribution of the molecular clouds in the Galaxy in the most detailed manner to date.

Stars are formed by molecular gas and dust coalescing in space. These molecular gases are so dilute and cold that they are invisible to the human eye, but they do emit faint radio waves that can be observed by radio telescopes.

Observing from Earth, a lot of matter lies ahead and behind these molecular clouds and these overlapping features m...

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Researchers use Artificial Intelligence to Predict Cardiovascular Disease

Researchers use artificial intelligence to predict cardiovascular disease
Study design, workflow, and bioinformatics. Overall research methodology includes, (1) clinical data analysis; (2) cohort building; (3) cardiovascular disease-based sample collection; (4) sample management and tracking; (5) RNA extraction, and high-throughput sequencing; (6) pipeline and bioinformatics application development for RNA-seq data processing, quality checking, gene-disease annotation, and phenotyping; and (7) implementation of artificial intelligence and machine learning techniques for predictive analysis. Credit: Genomics (2023). DOI: 10.1016/j.ygeno.2023.110584

Researchers may be able to predict cardiovascular disease — such as arterial fibrillation and heart failure — in patients by using artificial intelligence (AI) to examine the genes in their DNA, according to a new ...

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Researchers focus AI on Finding Exoplanets

Three young planets in orbit around an infant star known as HD 163296 (Photo credit: NRAO/AUI/NSF; S. Dagnello)

New research from the University of Georgia reveals that artificial intelligence can be used to find planets outside of our solar system. The recent study demonstrated that machine learning can be used to find exoplanets, information that could reshape how scientists detect and identify new planets very far from Earth.

“One of the novel things about this is analyzing environments where planets are still forming,” said Jason Terry, doctoral student in the UGA Franklin College of Arts and Sciences department of physics and astronomy and lead author on the study...

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Nanoscale Ferroelectric Semiconductor could Power AI and Post-Moore’s Law Computing on a Phone

Nanoscale ferroelectric semiconductor could power AI and post-Moore's Law computing on a phone
a) Cross-sectional HAADF-STEM image of the 5 nm thick ScAlN grown on Mo template. (b) and (c) Nano-beam electron diffraction patterns captured from the Mo (b) and ScAlN (c) regions labeled in (a). (d) Magnified HAADF-STEM image showing the thickness of the ScAlN layer. (e) Schematic of the epitaxial relationship between wz-ScAlN and bcc-Mo. (f) EDS element maps for the ITO/ScAlN/Mo capacitor. Credit: Applied Physics Letters (2023). DOI: 10.1063/5.0136265

Ferroelectric semiconductors are contenders for bridging mainstream computing with next generation architectures, and now a team at the University of Michigan has made them just five nanometers thick—a span of just 50 or so atoms.

This paves the way for integrating ferroelectric technologies with conventional components used in ...

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