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For the first time, scientists have used Earth-based telescopes funded by the U.S. National Science Foundation to look back over 13 billion years and measure how the first stars in the universe affected light emitted from the Big Bang. Using the NSF Cosmology Large Angular Scale Surveyor (NSF CLASS) telescopes in northern Chile, astrophysicists have measured this polarized microwave light to create a clearer picture of one of the least understood epochs in the history of the universe, the cosmic dawn.

The NSF CLASS telescopes are uniquely designed to detect the large-scale fingerprints left by the first stars in the relic Big Bang light — a feat that previously had only been accomplished by instruments in space. The findings will help better define signals coming from the residual glow of the Big Bang, or the cosmic microwave background, and form a clearer picture of the early universe. The research is led by Johns Hopkins University and The University of Chicago and published in The Astrophysical Journal.

“No other ground-based experiment can do what NSF CLASS is doing,” says Nigel Sharp, program director in the NSF Division of Astronomical Sciences, which has supported NSF CLASS for over 15 years. “The CLASS team has greatly improved measurement of the cosmic microwave polarization signal, and this impressive leap forward is a testament to the scientific value produced by

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With support from the U.S. National Science Foundation, researchers at the University of Houston have captured the dynamics of microscopic cholesterol crystal formation on video for the first time. Understanding these mechanisms could help scientists develop more effective treatments for managing high cholesterol, a condition that affects 25 million adults in the U.S., according to the U.S. Centers for Disease Control and Prevention. A better understanding of crystal formation could also enhance optoelectronics, which are electronic devices that work by controlling and sensing light.

NSF-supported researchers Jeffrey Rimer and Peter Vekilov are known for their work in crystal engineering and therapeutics that help prevent crystallization in human diseases. Their latest achievement shows the fundamental layered process involved in crystal formation in environments that mimic the human body. This is the first time anyone has taken images of the surface growth of cholesterol crystals in real time at near-molecular resolution. The study was published in the Proceedings of the National Academy of Science.

Cholesterol Crystal Formation

Credit: D. Chakraborty, W. Ma, X. Wang, Z. Chu, T. Yang, M. Warzecha, P.G. Vekilov, & J.D. Rimer.

Scientists have captured the first ever time-lapse video of the layered growth of a cholesterol monohydrate crystal.

Cholesterol crystals can build up in blood vessels or the gallbladder, causing blockages,

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Neurodegenerative diseases like Alzheimer’s are a growing concern in the U.S., with over 7 million Americans living with Alzheimer’s disease today. By 2060, that number is expected to grow, affecting nearly 13 million people. These diseases are not only hard on individuals and families, but are costly, with more than $230 billion spent in the U.S. each year in caregiving alone. As the population ages, the need for new ways to detect and address the silent emergence of these diseases has never been more urgent. 

New artificial intelligence predictive models used in brain research may provide a way to better predict how a person’s brain ages over time, helping doctors recognize warning signs long before clinical symptoms surface. 

Supported by the U.S. National Science Foundation, a team of researchers led by Paul Bogdan, an associate professor in the University of Southern California Department of Electrical and Computer Engineering, has developed a cutting-edge AI system capable of generating a future MRI of a person’s brain from just a single scan. This technology opens the door to identifying subtle changes that may signal the earliest stages of neurodegenerative diseases — potentially years before traditional diagnostic methods could detect them.

To build the tool, the team combined two advanced AI techniques: a 3D diffusion model and a ControlNet, which allow the system to “control” or guide image generation

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The U.S. National Science Foundation today announced a new funding opportunity to support research and technology development that will improve the next generation of wireless communication systems known as NextG.     In collaboration with industry, other government agencies, and international partners, the NSF Verticals-enabling Intelligent NEtwork  Systems (NSF VINES) program will invest up to $100 million to accelerate performance and capabilities of next-generation (NextG) advanced intelligent network systems  spanning the user-edge-core-cloud continuum. 

“NSF VINES will enhance U.S. competitiveness in advanced telecommunications technologies, including NextG wireless telecommunications and emerging potential NextG vertical industries, and prepare the American workforce for jobs available now and in the future,” said Brian Stone, performing the duties of the NSF Director.

“This important investment from NSF, in collaboration with industry and other government agencies, will help strengthen U.S. leadership and ensure the American people reap the benefits in areas such as self-driving cars, advanced manufacturing, energy infrastructure, and beyond,” said Dr. Lynne Parker, Principal Deputy Director of The White House Office of Science and Technology Policy. 

NSF VINES is in partnership with several major industry organizations and U.S. federal agencies, including Ericsson, Intel, Qualcomm, the U.S. Department of Homeland Security, U.S. Department of Defense Office of the Under Secretary for Research and Engineering, and U.S. Department of Commerce National Institute of Standards and Technology, as well as international partners from

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