Lifeboat Foundation: Safeguarding Humanity
Toggle light / dark theme

Blog – Page 4599

Gas stoves in California homes are leaking cancer-causing benzene, researchers found in a new study published on Thursday, though they say more research is needed to understand how many homes have leaks.

In the study, published in Environmental Science and Technology on Thursday, researchers also estimated that over 4 tons of benzene per year are being leaked into the atmosphere from outdoor pipes that deliver the gas to buildings around California — the equivalent to the benzene emissions from nearly 60,000 vehicles. And those emissions are unaccounted for by the state.

The researchers collected samples of gas from 159 homes in different regions of California and measured to see what types of gases were being emitted into homes when stoves were off. They found that all of the samples they tested had hazardous air pollutants, like benzene, toluene, ethylbenzene and xylene (BTEX), all of which can have adverse health effects in humans with chronic exposure or acute exposure in larger amounts.

Read more | >

A single computer chip has transmitted a record 1.84 petabits of data per second via a fibre-optic cable – enough bandwidth to download 230 million photographs in that time, and more traffic than travels through the entire internet’s backbone network per second.

Asbjørn Arvad Jørgensen at the Technical University of Denmark in Copenhagen and his colleagues have used a photonic chip – a technology that allows optical components to be built onto computer chips – to divide a stream of data into thousands of separate channels and transmit them all at once over 7.9 kilometres.

First, the team split the data stream into 37 sections, each of which was sent down a separate core of the fibre-optic cable. Next, each of these channels was split into 223 data chunks that existed in individual slices of the electromagnetic spectrum. This “frequency comb” of equidistant spikes of light across the spectrum allowed data to be transmitted in different colours at the same time without interfering with each other, massively increasing the capacity of each core.

Read more | >

Summary: In a highly competitive environment, Trinidadian killifish grow larger brains. This neuro-evolution allows for greater fitness and survival rates.

Source: UT Arlington.

In response to a high-competition environment, Trinidadian killifish evolve larger brains, increasing their fitness and survival rates, according to a new study in Ecology Letters by biologists at The University of Texas at Arlington.

Read more | >

NASA continues to outdo itself with the majestic images of space that it keeps releasing – but even by the agency’s high standards, a 12-year timelapse of the entirety of the night sky is an impressive achievement.

The imagery has been captured over those years by the NEOWISE (Near-Earth Object Wide Field Infrared Survey Explorer) space telescope, which was originally launched in 2009 under the previous name ‘WISE’ to study the Universe outside of our Solar System.

It has since been repurposed, and renamed, to track near-Earth objects including asteroids and comets.

Read more | >

While automated manufacturing is ubiquitous today, it was once a nascent field birthed by inventors such as Oliver Evans, who is credited with creating the first fully automated industrial process, in flour mill he built and gradually automated in the late 1700s. The processes for creating automated structures or machines are still very top-down, requiring humans, factories, or robots to do the assembling and making.

However, the way nature does assembly is ubiquitously bottom-up; animals and plants are self-assembled at a cellular level, relying on proteins to self-fold into target geometries that encode all the different functions that keep us ticking. For a more bio-inspired, bottom-up approach to assembly, then, human-architected materials need to do better on their own. Making them scalable, selective, and reprogrammable in a way that could mimic nature’s versatility means some teething problems, though.

Now, researchers from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) have attempted to get over these growing pains with a new method: introducing magnetically reprogrammable materials that they coat different parts with—like robotic cubes—to let them self-assemble. Key to their process is a way to make these magnetic programs highly selective about what they connect with, enabling robust self-assembly into specific shapes and chosen configurations.

Read more | >

Ask a smart home device for the weather forecast, and it takes several seconds for the device to respond. One reason this latency occurs is because connected devices don’t have enough memory or power to store and run the enormous machine-learning models needed for the device to understand what a user is asking of it. The model is stored in a data center that may be hundreds of miles away, where the answer is computed and sent to the device.

MIT researchers have created a new method for computing directly on these devices, which drastically reduces this latency. Their technique shifts the memory-intensive steps of running a machine-learning model to a central server where components of the model are encoded onto light waves.

The waves are transmitted to a connected device using , which enables tons of data to be sent lightning-fast through a network. The receiver then employs a simple optical device that rapidly performs computations using the parts of a model carried by those light waves.

Read more | >