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Researchers in Australia have developed a new technology that uses infrared imaging to allow people to see clearly in the dark. These ultra-thin films could one day turn regular spectacles into night-vision goggles and also revolutionise several sectors, such as autonomous vehicle navigation, optical tomography, and food quality control. The film is thinner than human hair and is made of nanoscale crystals. Researchers from the Australian National University (ANU) say the prototype tech could replace the bulky night-vision goggles used by military and law-enforcement officials with a lightweight alternative, and could also make it safer to drive at night or walk home after dark.

The technology, which works at room temperature, converts infrared light into light visible to the human eye. Researchers say it’s cheap and easy to produce at a mass scale, making it a preferred choice over the current high-end infrared imaging tech that requires cryogenic freezing and is costly to produce.

The first-of-its-kind thin film has been described in a new report published in the journal Advanced Photonics. It could be very useful to security personnel who currently use the heavy helmet-mounted night vision goggles that they say have led to neck pain.

“We have made the invisible visible,” lead researcher Dr. Rocio Camacho Morales said in a report published on the ANU website. “Our technology is able to transform infrared light, normally invisible to the human eye, and turn this into images people can clearly see — even at distance.”

Dragomir Neshev, a professor in physics at the university, said this was the first time that infrared light has been successfully transformed into visible images in an ultra-thin screen, and called it a “really exciting development”.

The scientists, who had received help from European and British researchers on this project, are now working to advance the technology further. It’s not yet clear when the technology would be available for commercial use.


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Earth’s Spin to Speed Up Briefly, Causing Shorter Days This Summer

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Earth’s Spin to Speed Up Briefly, Causing Shorter Days This Summer

Reports indicate that for three days this summer – July 9, July 22 and August 5 – Earth’s rotation will speed up slightly, trimming 1.3 to 1.5 milliseconds off each day. Imperceptible in everyday life, this shift underscores how the Moon’s position influences our planet’s spin. For reference, the shortest day on record was July 5, 2024, lasting 1.66 milliseconds less than 24 hours. Over billions of years Earth’s rotation has slowly lengthened, but recent data show speedups. Scientists say monitoring these tiny changes is important for understanding Earth’s dynamics and timekeeping.

Causes of Faster Spin

According to timeanddate.com, the shortest-ever recorded day was on July 5, 2024, which was 1.66 milliseconds shy of 24 hours. The acceleration is largely driven by the Moon’s gravity. On those dates (July 9, July 22 and August 5), the Moon will lie far north or south of Earth’s equator, weakening its tidal braking on our planet’s spin. As a result, Earth rotates a bit faster – like spinning a top held at its ends. Seasonal shifts in mass distribution also affect rotation. Richard Holme of the University of Liverpool notes that summer growth and melting snow in the Northern Hemisphere move mass outward from Earth’s axis, slowing the spin in the same way an ice skater slows by extending her arms.

Timekeeping and Technology

Shifts in day length are handled by precise timekeeping. The International Earth Rotation and Reference Systems Service (IERS) monitors Earth’s spin and adds leap seconds to keep Coordinated Universal Time (UTC) in sync with solar time. Normally a second is added when Earth’s rotation slows, but if the spin-up trend continues, scientists have floated a “negative leap second” – removing a second – to realign clocks.

Dr. Michael Wouters of Australia’s National Measurement Institute says this fix would be unprecedented, and notes that even if a few seconds accumulated over decades, it would likely go unnoticed. Dr. David Gozzard of the University of Western Australia points out that GPS satellites, communications networks and power grids rely on atomic clocks synced to nanoseconds, and that millisecond-scale changes in Earth’s rotation are easily absorbed by these systems.

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James Webb Telescope Spots Rare ‘Cosmic Owl’ Formed by Colliding Galaxies

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James Webb Telescope Spots Rare ‘Cosmic Owl’ Formed by Colliding Galaxies

NASA’s James Webb Space Telescope has captured the “Cosmic Owl,” a startling owl-faced pair of colliding ring galaxies. This double-ring structure is exceptionally rare: ring galaxies account for just 0.01% of known galaxies, and two colliding rings is almost unheard of. The JWST image provides an exceptional natural laboratory for studying galaxy evolution. Models suggest the galactic clash began roughly 38 million years ago, meaning the owl-like shape could persist for a long time. A team led by Ph.D. student Mingyu Li of Tsinghua University in China announced the finding.

Spotting the ‘Cosmic Owl’

According to Mingyu Li, the first author of the new study , he and his team found the Owl by combing through public JWST data from the COSMOS field. The twin ring galaxies jumped out thanks to JWST’s infrared imaging. Each ring is about 26,000 light-years across (a quarter of the Milky Way), and each harbors a supermassive black hole at its core – one of the Owl’s eyes.

JWST images show the collision interface – the Owl’s beak – ablaze with activity. ALMA observations find a huge clump of molecular gas there – the raw fuel for new stars – being squeezed by the impact. Radio observations show a jet from one galaxy’s black hole slamming into the gas. Li notes the shockwave-plus-jet have ignited an intense starburst, turning the beak into a stellar nursery.

Rarity and Significance

Ring galaxies are extremely rare (≈0.01% of all galaxies), so finding two in collision is unheard of. Another team independently identified the same system and called it the “Infinity Galaxy”. Li says this event is an exceptional natural laboratory for studying galaxy evolution. In one view, researchers can see black holes feeding, gas compressing and starbursts happening together.

Li points out the collision’s shockwave and jet have triggered an intense starburst in the beak. He says this may be a crucial way to turn gas into stars rapidly, which could help explain how young galaxies built up their mass so quickly. Simulations will clarify the precise collision conditions needed to produce such a rare twin-ring “owl” shape.

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MIT Develops Low-Resource AI System to Control Soft Robots with Just One Image

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MIT Develops Low-Resource AI System to Control Soft Robots with Just One Image

The use of conventional robots for industry and hazardous environments is easy for the purpose of control and modelling. However, these are too rigid to operate in confined places and uneven terrain. The soft bio-related roots are better adapted to the environment and manoeuvring in inaccessible places. Such flexible capabilities would need an array of on-board sensors and spacious models which are tailored to each robot design. Having a new and less resource-demanding approach, the researchers at MIT have developed a far less complex, deep learning control system that teaches the soft, bio-inspired robots to follow the command from a single image only.

Soft Robots Learn from a Single Image

As per Phys.org, this research has been published in the journal Nature, by training a deep neural network on two to three hours of multi-view images of various robots executing random commands, the scientists trained the network to reconstruct the range and shape of mobility from only one image. The previous machine learning control designs need customised and costly motion systems. Lack of a general-purpose control system limited the applications and made prototyping less practical.

The methods unshackle the robotics hardware design from the ability to model it manually. This has dictated precision manufacturing, extensive sensing capabilities, costly materials and reliance on conventional and rigid building blocks.

AI Cuts Costly Sensors and Complex Models

The single camera machine learning approach allows the high-precision control in tests on a variety of robotic systems, adding the 3D-printed pneumatic hand, 16-DOF Allegro hand, a soft auxetic wrist and a low-cost Poppy robot arm.

As this system depends on the vision alone, it might not be suitable for more nimble tasks which need contact sensing and tactile dynamics. The performance may also degrade in cases where visual cues are not enough.

Researchers suggest the addition of sensors and tactile materials that can enable the robots to perform different and complex tasks. There is also potential to automate the control of a wider range of robots, together with minimal or no embedded sensors.

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