We’ve detected that JavaScript is disabled in this browser. Please enable JavaScript or switch to a supported browser to continue using x.com. You can see a list of supported browsers in our Help Center.
Terms of Service Privacy Policy Cookie Policy Imprint Ads info © 2024 X Corp.
The first images are back from a spacecraft that, on Sept. 4, got to within just 102.5 miles (165 kilometers) of the surface of Mercury, the closest it will ever get. The European Space Agency’s $1.8 billion BepiColombo vehicle snapped images of the inner planet’s polar regions and cratered surface as it zoomed by.
The flyby was the seventh of its long journey around the solar system—one of Earth, two of Venus and three of Mercury—as it attempts to lose energy and steer itself into orbit around Mercury during a long and complex journey. This latest flyby reduced the spacecraft’s speed and changed its direction.
During the flyby, which culminated at 21:48 UTC on Sept. 4, BepiColombo took images and tested 10 scientific instruments, which included taking measurements of how the solar wind interacts with the planet’s magnetic field.
Their…
A multi-university research team co-led by University of Virginia engineering professor Gustavo K. Rohde has developed a system that can spot genetic markers of autism in brain images with 89 to 95% accuracy.
Their findings suggest doctors may one day see, classify and treat autism and related neurological conditions with this method, without having to rely on, or wait for, behavioral cues. And that means this truly personalized medicine could result in earlier interventions.
For the Artemis 3 mission, we will be able to reach astronauts up to 2 kilometers away from the lander.
COPENHAGEN, Denmark — In the never-ending quest to unlock the secrets of a long and healthy life, researchers at the University of Copenhagen have made a remarkable discovery. Their study has identified a specific gene that plays a crucial role in extending longevity across various species, including humans.
Publishing their work in the journal Cell Reports, researchers say the gene in question is called OSER1, and it encodes a protein that the team has dubbed a “novel pro-longevity factor.”
“We identified this protein that can extend longevity. It is a novel pro-longevity factor, and it is a protein that exists in various animals, such as fruit flies, nematodes, silkworms, and in humans,” says Professor Lene Juel Rasmussen, the senior author behind the study, in a media release.
China’s investment is driven by a need to secure a stable supply of chips critical to various industries, which is why over a dozen Chinese fabs are coming online in 2024 and 2025. Therefore, this surge in spending is not limited to the country’s top-tier manufacturers, such as Semiconductor Manufacturing International Corp. (SMIC) and Hua Hong, but also includes significant contributions from smaller and mid-sized chipmakers. These investments enabled China to maintain its position as the world’s largest market for chipmaking equipment. Virtually all new Chinese fabs are focused on trailing nodes, as it is hard for Chinese companies to get the advanced tools required to make chips on leading-edge process technologies.
China is the only major market to increase its spending on fab tools compared to the previous year despite a global economic slowdown. In contrast, Taiwan, South Korea, and North America all reduced their investments in wafer fab equipment during the same period.
The spending surge in China has also significantly impacted chipmaking tool makers. Companies like Applied Materials, Lam Research, KLA from the U.S., Tokyo Electron from Japan, and ASML from the Netherlands have all reported increased revenue contributions from Chinese companies. Such contributions range from 32% at Applied to 49% at ASML.
The world keeps time with the ticks of atomic clocks, but a new type of clock under development—a nuclear clock—could revolutionize how we measure time and probe fundamental physics.
Now imagine a frequency mixer that works at a quadrillion (PHz, petahertz) times per second—up to a million times faster. This frequency range corresponds to the oscillations of the electric and magnetic fields that make up light waves.
Petahertz-frequency mixers would allow us to shift signals up to optical frequencies and then back down to more conventional electronic frequencies, enabling the transmission and processing of vastly larger amounts of information at many times higher speeds. This leap in speed isn’t just about doing things faster; it’s about enabling entirely new capabilities.
Lightwave electronics (or petahertz electronics) is an emerging field that aims to integrate optical and electronic systems at incredibly high speeds, leveraging the ultrafast oscillations of light fields. The key idea is to harness the electric field of light waves, which oscillate on sub-femtosecond (10-15 seconds) timescales, to directly drive electronic processes.
Magnetic confinement fusion devices are technologies that can attain controlled nuclear fusion reactions, using magnetic fields to confine hot plasmas. These devices could contribute to the ongoing transition towards more sustainable energy production methods.
Butterflies can see more of the world than humans, including more colors and the field oscillation direction, or polarization, of light. This special ability enables them to navigate with precision, forage for food and communicate with one another. Other species, like the mantis shrimp, can sense an even wider spectrum of light, as well as the circular polarization, or spinning states, of light waves. They use this capability to signal a “love code,” which helps them find and be discovered by mates.
Inspired by these abilities in the animal kingdom, a team of researchers at the Penn State College of Engineering has developed an ultrathin optical element known as a metasurface, which can attach to a conventional camera and encode the spectral and polarization data of images captured in a snapshot or video through tiny, antenna-like nanostructures that tailor light properties. A machine learning framework, also developed by the team, then decodes this multi-dimensional visual information in real-time on a standard laptop.
The researchers have published their work in Science Advances.
