Lifeboat Foundation

Faster, smaller, smarter and more energy-efficient chips for everything from consumer electronics to big data to brain-inspired computing could soon be on the way after engineers at The University of Texas at Austin created the smallest memory device yet. And in the process, they figured out the physics dynamic that unlocks dense memory storage capabilities for these tiny devices.

The research published recently in Nature Nanotechnology builds on a discovery from two years ago, when the researchers created what was then the thinnest memory storage device. In this new work, the researchers reduced the size even further, shrinking the cross section area down to just a single square nanometer.

Getting a handle on the physics that pack dense memory storage capability into these devices enabled the ability to make them much smaller. Defects, or holes in the material, provide the key to unlocking the high-density memory storage capability.

Since Xi put out the call to build up the new area, China’s tech giants have piled in. Alibaba Group Holding, Tencent Holdings, Baidu, Zhongguancun Science Park and Tsinghua University have all established projects in Xiongan. The projects include the use of sensors, 5G networks and facilities for supercomputing and big data in the pursuit of building up the smart city. Alibaba is the parent company of the Post.

JD Digits, the e-commerce giant’s big data arm, is building a smart city operating system that uses artificial intelligence for urban management.

Scientists at Osaka University develop a label-free method for identifying respiratory viruses based on changes in electrical current when they pass through silicon nanopores, which may lead to new rapid COVID-19 tests.

The ongoing global pandemic has created an urgent need for rapid tests that can diagnose the presence of the SARS-CoV-2 virus, the pathogen that causes COVID-19, and distinguish it from other respiratory viruses. Now, researchers from Japan have demonstrated a new system for single-virion identification of common respiratory pathogens using a machine learning algorithm trained on changes in current across silicon nanopores. This work may lead to fast and accurate screening tests for diseases like COVID-19 and influenza.

In a study published this month in ACS Sensors scientists at Osaka University have introduced a new system using silicon nanopores sensitive enough to detect even a single virus particle when coupled with a machine learning algorithm.

With fall and winter holidays coming up, many will be pondering the relationship between food and sleep. Researchers led by Professor Masashi Yanagisawa at the University of Tsukuba in Japan hope they can focus people on the important middlemen in the equation: bacterial microbes in the gut. Their detailed study in mice revealed the extent to which bacteria can change the environment and contents of the intestines, which ultimately impacts behaviors like sleep.

The experiment itself was fairly simple. The researchers gave a group of mice a powerful cocktail of antibiotics for four weeks, which depleted them of intestinal microorganisms. Then, they compared intestinal contents between these mice and control mice who had the same diet. Digestion breaks food down into bits and pieces called metabolites. The research team found significant differences between metabolites in the microbiota-depleted mice and the control mice. As Professor Yanagisawa explains, “we found more than 200 metabolite differences between mouse groups. About 60 normal metabolites were missing in the microbiota-depleted mice, and the others differed in the amount, some more and some less than in the control mice.”

The team next set out to determine what these metabolites normally do. Using metabolome set enrichment analysis, they found that the biological pathways most affected by the antibiotic treatment were those involved in making neurotransmitters, the molecules that cells in the brain use to communicate with each other. For example, the tryptophan–serotonin pathway was almost totally shut down; the microbiota-depleted mice had more tryptophan than controls, but almost zero serotonin. This shows that without important gut microbes, the mice could not make any serotonin from the tryptophan they were eating. The team also found that the mice were deficient in vitamin B6 metabolites, which accelerate production of the neurotransmitters serotonin and dopamine.

Code Unto Caesar

Durendal’s algorithm wrote scripture about three topics: “the plague,” “Caesar,” and “the end of days.” So it’s not surprising that things took a grim turn. The full text is full of glitches characteristic of AI-written texts, like excerpts where over half of the nouns are “Lord.” But some passages are more coherent and read like bizarre doomsday prophecies.

For example, from the plague section: “O LORD of hosts, the God of Israel; When they saw the angel of the Lord above all the brethren which were in the wilderness, and the soldiers of the prophets shall be ashamed of men.”

Scientists from NASA ’s Goddard Space Flight Center in Greenbelt, Maryland, and international collaborators demonstrated a new method for mapping the location and size of trees growing outside of forests, discovering billions of trees in arid and semi-arid regions and laying the groundwork for more accurate global measurement of carbon storage on land.

Using powerful supercomputers and machine learning algorithms, the team mapped the crown diameter – the width of a tree when viewed from above – of more than 1.8 billion trees across an area of more than 500,000 square miles, or 1,300,000 square kilometers. The team mapped how tree crown diameter, coverage, and density varied depending on rainfall and land use.

Like walking and breathing and could one day allow people to control prosthetics simply by thinking…

The US Army is funding a project that could lead to brain-machine interfaces. It includes an algorithm capable of isolating brain signals and linking them to specific behaviors such as walking and breathing.

Continue reading “Army-funded algorithm decodes brain signals responsible for behaviors” »

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Although many different approaches have been proposed to address this problem, it’s clear that any sustainable, long-term solution will include one important component: a transition to energy sources that don’t result in additional carbon dioxide emissions. While most of the ideas put forth — such as the hypothetical Green New Deal — focus on renewable energy sources like solar and wind power, there’s another option that we should seriously reconsider: nuclear fission power.

As we embrace green solutions, nuclear should absolutely be part of the equation.