Lifeboat Foundation

Researchers have improved a naturally-occurring enzyme to enhance its plastic-eating abilities. The modified enzyme, which can digest strong plastic used in bottles, could help in the fight against pollution.

Researchers in the US and Britain have engineered a plastic-eating enzyme to speed up its abilities to digest plastic.

Scientists from Britain’s University of Portsmouth and the US Department of Energy’s National Renewable Energy Laboratory “tweaked” the structure of the naturally-occurring enzyme after they found that it was helping a bacteria to break down, or digest, plastic used to make bottles.

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This 9,920 pound steel bridge was 3D printed in midair.

A new study has found that thousands of Android apps are violating U.S. law by tracking and sharing the data of children.

This artist’s impression shows the light of several distant quasars piercing the northern half of the Fermi Bubbles, an outflow of gas expelled by the supermassive black hole in the centre of the Milky Way. The NASA/ESA Hubble Space Telescope probed the quasars’ light for information on the speed of the gas and whether the gas is moving toward or away from Earth. Based on the material’s speed, the research team estimated that the bubbles formed from an energetic event between 6 million and 9 million years ago.

The inset diagram at bottom left shows the measurement of gas moving toward and away from Earth, indicating the material is traveling at a high velocity.

Hubble also observed light from quasars that passed outside the northern bubble. The box at upper right reveals that the gas in one such quasar’s light path is not moving toward or away from Earth. This gas is in the disc of the Milky Way and does not share the same characteristics as the material probed inside the bubble.

Elon Musk’s Space Exploration Technologies Corp. will build its giant in-development rocket, nicknamed “BFR,” at the Port of Los Angeles.

X-ray observations have revealed a dozen stellar-mass black holes at the centre of the Galaxy, implying that there are thousands more to be found. The discovery confirms a fundamental prediction of stellar dynamics.

Using supercomputer modeling, University of Oregon scientists have unveiled a new explanation for the geology underlying recent seismic imaging of magma bodies below Yellowstone National Park.

Yellowstone, a supervolcano famous for explosive eruptions, large calderas and extensive lava flows, has for years attracted the attention of scientists trying to understand the location and size of magma chambers below it. The last caldera forming eruption occurred 630,000 years ago; the last large volume of lava surfaced 70,000 years ago.

Crust below the park is heated and softened by continuous infusions of magma that rise from an anomaly called a mantle plume, similar to the source of the magma at Hawaii’s Kilauea volcano. Huge amounts of water that fuel the dramatic geysers and hot springs at Yellowstone cool the crust and prevent it from becoming too hot.

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Army researchers have developed an artificial intelligence and machine learning technique that produces a visible face image from a thermal image of a person’s face captured in low-light or nighttime conditions. This development could lead to enhanced real-time biometrics and post-mission forensic analysis for covert nighttime operations.

Thermal cameras like FLIR, or Forward Looking Infrared, sensors are actively deployed on aerial and ground vehicles, in watch towers and at check points for surveillance purposes. More recently, thermal cameras are becoming available for use as body-worn cameras. The ability to perform automatic face recognition at nighttime using such thermal cameras is beneficial for informing a Soldier that an individual is someone of interest, like someone who may be on a watch list.

The motivations for this technology—developed by Drs. Benjamin S. Riggan, Nathaniel J. Short and Shuowen “Sean” Hu, from the U.S. Army Research Laboratory—are to enhance both automatic and human-matching capabilities.

Serotonin influences the way humans make decisions. If scientists replicate this in an artificial intelligence system, depression could be a side-effect.