Lifeboat Foundation

High-resolution recordings of electrical signals from the surface of the brain could improve surgeons’ ability to remove brain tumors and treat epilepsy, and could open up new possibilities for medium-and longer-term brain-computer interfaces.

A team of engineers, surgeons, and medical researchers has published data from both humans and rats demonstrating that a new array of brain sensors can record electrical signals directly from the surface of the human brain in record-breaking detail. The new brain sensors feature densely packed grids of either 1,024 or 2,048 embedded electrocorticography (ECoG) sensors. The paper was published by the journal Science Translational Medicine on January 19, 2022.

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A surprising property of how resonant photons interact with an absorbing medium has been uncovered by physicists in Canada. They say they have found that even photons passing straight through the medium energize atoms within it, causing atoms to spend nearly as much time in their excited states as those that have absorbed photons. They see their result as a challenge to theorists trying to describe how light interacts with matter quantum mechanically.

Aephraim Steinberg and colleagues at the University of Toronto made the discovery while investigating what happens to a beam of photons passing through a cloud of atoms when the photons’ frequency is equal to that of one of the atomic transitions. Intuitively, they say, it would be expected that those photons exciting atoms within the cloud would be absorbed and then at best re-emitted in a random direction. As such, the flux of photons coming from excited atoms that are detected in the forward direction would be miniscule.

Indeed, they point out, this idea that only absorbed, or “lost”, photons contribute to the excitation springs naturally from theory that tells us the total time atoms spend in the excited state is directly proportional to the number of photons that are lost.

A team of astrophysicists has created a simulated image that shows how the Nancy Grace Roman Space Telescope could conduct a mega-exposure similar to but far larger than Hubble’s celebrated Ultra Deep Field Image. This Hubble observation transformed our view of the early universe, revealing galaxies that formed just a few hundred million years after the big bang.

“Roman has the unique ability to image very large areas of the sky, which allows us to see the environments around galaxies in the early universe,” said Nicole Drakos, a postdoctoral scholar at the University of California Santa Cruz, who led the study. “Our study helps demonstrate what a Roman ultra-deep field could tell us about the universe, while providing a tool for the scientific community to extract the most value from such a program.”

Church points to factors that helped make such a success of three of the top COVID-19 vaccine technologies. For one thing, they all used gene therapy technologies, and each was a new method relative to the past and to each other. For instance, the AstraZeneca vaccine was based on an adenovirus capsid containing double-stranded DNA as opposed to an adeno-associated virus (AAV) of the Johnson & Johnson/Janssen vaccine, while the Moderna and Pfizer/BioNTech vaccines were based on single-stranded mRNA inside lipid nanoparticles.

“Implementation science is the unsung handmaiden of biomedical discovery!”

Secondly, each of them was approved by the FDA 10 times faster than the vast majority of therapeutic products, and finally, the cost per vaccine has been as low as $2 per dose for the United Nations’ COVAX global access program. That’s about a million times cheaper than Zolgensma, he says, referring to the AAV gene therapy medication used to treat spinal muscular atrophy. So since “any one of these could spark a revolution,” according to Church, imagine what could happen in the next 12 months if all four factors pertain again?

Samsung, the world’s biggest memory chip maker, has announced that it has become the first in the world to demonstrate the MRAM (Magnetoresistive Random Access Memory) technology for in-memory computing. The company’s paper on its innovation, titled ‘A crossbar array of magnetoresistive memory devices for in-memory computing,’ was published by Nature on its website, and its print edition is coming next.

The research was a collaboration between SAIT (Samsung Advanced Institute of Technology), Samsung Foundry, and Samsung Semiconductor R&D. Dr. Seungchul Jung (Staff Researcher at SAIT), Dr. Donhee Ham (Fellow of SAIT and Professor of Harvard University), and Dr. Sang Joon Kim (Vice President of Technology at SAIT) worked on the research.

Usually, data is stored in memory chips (DRAM) and processed by a CPU or an AP (Application Processor). However, data storage and computing happen on the same chip with in-memory computing. Since there is no need to transfer data from memory to the processor and vice versa, a lot of time is saved. Data processing inside the memory happens in a highly parallel manner, resulting in substantial power savings. Samsung claims that MRAM technology will be great for things like AI processing.

The Federal Reserve took its first step toward more seriously examining issuing a central bank digital currency, releasing a report on Thursday that examines the idea’s potential costs and benefits and opening the door for public comment.

In a long-awaited report, the Fed avoided taking sides and set out a list of arguments for and against a digital currency, and posed questions that will shape the debate.

“We look forward to engaging with the public, elected representatives and a broad range of stakeholders as we examine the positives and negatives of a central bank digital currency in the United States,” Jerome H. Powell, the Fed chair, said in a statement. Mr. Powell had previewed that a report would be forthcoming in May 2021.

The energy systems that power our lives also produce wasted heat—like heat that radiates off hot water pipes in buildings and exhaust pipes on vehicles. A new flexible thermoelectric generator can wrap around pipes and other hot surfaces and convert wasted heat into electricity more efficiently than previously possible, according to scientists at Penn State and the National Renewable Energy Laboratory.

“A large amount of heat from the energy we consume is essentially being thrown away, often dispersed right into the atmosphere,” said Shashank Priya, associate vice president for research and professor of materials science and engineering at Penn State. “We haven’t had cost-effective ways with conformal shapes to trap and convert that heat to useable energy. This research opens that door.”

Penn State researchers have been working to improve the performance of thermoelectric generators—devices that can convert differences in temperature to electricity. When the devices are placed near a heat source, electrons moving from the hot side to the cold side produce an electric current, the scientists said.

Researchers created a biocompatible graphene ink and used household printers to make electronic components.

Scientists in Ireland have developed a new low-cost method to produce graphene, which could accelerate adoption of the strong and light ‘wonder material’.

Researchers at Trinity College Dublin’s School of Physics and AMBER, the Science Foundation Ireland research centre for advanced materials, teamed up with colleagues in the UK and Norway to develop a scalable graphene production method.

Artificial intelligence and machine learning are currently affecting our lives in many small but impactful ways. For example, AI and machine learning applications recommend entertainment we might enjoy through streaming services such as Netflix and Spotify.

In the near future, it’s predicted that these technologies will have an even larger impact on society through activities such as driving fully autonomous vehicles, enabling complex scientific research and facilitating medical discoveries.

But the computers used for AI and machine learning demand a lot of energy. Currently, the need for computing power related to these technologies is doubling roughly every three to four months. And cloud computing data centers used by AI and machine learning applications worldwide are already devouring more electrical power per year than some small countries. It’s easy to see that this level of energy consumption is unsustainable.