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Blog – Page 1114

A research team from Japan, including scientists from Hitachi, Ltd. (TSE 6,501, Hitachi), Kyushu University, RIKEN, and HREM Research Inc. (HREM), has achieved a major breakthrough in the observation of magnetic fields at unimaginably small scales.

In collaboration with National Institute of Advanced Industrial Science and Technology (AIST) and the National Institute for Materials Science (NIMS), the team used Hitachi’s atomic-resolution holography electron microscope—with a newly developed image acquisition technology and defocus correction algorithms—to visualize the magnetic fields of individual atomic layers within a crystalline solid.

Many advances in , catalysis, transportation, and have been made possible by the development and adoption of high-performance materials with tailored characteristics. Atom arrangement and electron behavior are among the most critical factors that dictate a crystalline material’s properties.

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A combined team of roboticists from Stanford University and the Toyota Research Institute has found that adding audio data to visual data when training robots helps to improve their learning skills. The team has posted their research on the arXiv preprint server.

The researchers noted that virtually all training done with AI-based robots involves exposing them to a large amount of visual information, while ignoring associated audio. They wondered if adding microphones to robots and allowing them to collect data regarding how something is supposed to sound as it is being done might help them learn a task better.

For example, if a is supposed to learn how to open a box of cereal and fill a bowl with it, it may be helpful to hear the sounds of a box being opened and the dryness of the cereal as it cascades down into a bowl. To find out, the team designed and carried out four robot-learning experiments.

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India’s first space-based solar observatory, Aditya-L1, successfully completed its first halo orbit around the Sun-Earth L1 Lagrangian point, Isro announced on Monday. The observatory was launched on September 2, 2023, and was inserted into its targeted halo orbit on January 6, 2024. This achievement demonstrates the spacecraft’s capacity to maintain its complex trajectory. Aditya-L1 performed its first two manoeuvres on February 22 and June 7, 2024. The third manoeuvre, conducted on July 2, 2024, ensured the spacecraft’s transition into its second halo orbit around L1.

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Kratos Defense & Security Solutions (Kratos) has announced the successful test flight of its Erinyes hypersonic test vehicle.

Developed by the company’s Space & Missile Defense Systems Business Unit, the test was completed on June 12, 2024, according to the announcement.

The test vehicle reached Mach 5 in its first test flight. Erinyes is being developed under the auspices of the Missile Defense Agency (MDA) and the Naval Surface Warfare Center (NSWC).

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An archaeological team in Venezuela has uncovered 20 ancient rock art sites in Canaima National Park in the southeastern part of the country, consisting of both pictograms and petroglyphs, estimated to be about 4,000 years old.

This discovery reveals a previously unknown culture, even though similar rock art has been found elsewhere in South America.

The newfound rock art, referred to as pictograms, was painted in red and featured geometric shapes such as dotted lines, rows of X’s, star-shaped patterns, and interconnected straight lines. Additionally, there are simple depictions of leaves and stick figure drawings of people. Some images, known as petroglyphs, were incised into the rock and exhibit similar geometric designs.

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One of the primary goals of the Large Hadron Collider (LHC) experiments is to look for signs of new particles, which could explain many of the unsolved mysteries in physics. Often, searches for new physics are designed to look for one specific type of new particle at a time, using theoretical predictions as a guide. But what about searching for unpredicted – and unexpected – new particles?

Sifting through the billions of collisions that occur in the LHC experiments without knowing exactly what to look for would be a mammoth task for physicists. So, instead of combing through the data and looking for anomalies, the ATLAS and CMS collaborations are letting artificial intelligence (AI) streamline the process.

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