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Magnetic solids can be demagnetized quickly with a short laser pulse, and there are already so-called HAMR (Heat Assisted Magnetic Recording) memories on the market that function according to this principle. However, the microscopic mechanisms of ultrafast demagnetization remain unclear. Now, a team at HZB has developed a new method at BESSY II to quantify one of these mechanisms and they have applied it to the rare-earth element Gadolinium, whose magnetic properties are caused by electrons on both the 4f and the 5d shells. This study completes a series of experiments done by the team on nickel and iron-nickel alloys. Understanding these mechanisms is useful for developing ultrafast data storage devices.

New materials should make information processing more efficient, for example, through ultrafast spintronic devices that store data with less energy input. But to date, the microscopic mechanisms of ultrafast demagnetization are not fully understood. Typically, the process of demagnetization is studied by sending an ultrashort laser pulse to the sample, thereby heating it up, and then analyzing how the system evolves in the first picoseconds afterward.

For most of the time since the first description of multiple sclerosis (MS) in 1,868 the causes of this disabling disease have remained uncertain. Genes have been identified as important, which is why having other family members with MS is associated with a greater risk of developing the disease.

A recent study my colleagues and I conducted found that several types of infection during the teenage years are associated with MS after age 20. Our study didn’t investigate whether people who are more likely to have genetic risks for MS were also more likely to have worse infections.

This might explain why people with MS also have more infections that need hospital treatment.

Based on a rolling five-year average of announced investments, AlixPartners expects companies to invest $330 billion in the next five years throughout the EV supply chain globally. About a third of that is expected to be for batteries, largely in the China and Europe, while the U.S. attempts to catch up.

That forecast is up by 65% from an expected $200 billion from 2,018 according to Kumar.

“Electrification is occurring faster than many were thinking even a few years ago,” he said. “The plans OEMs have in place have started to change dramatically.”

In 2,021 Instagram will be the most popular social media platform. Recent statistics show that the platform now boasts over 1 billion monthly active users. With this many eyes on their content, influencers can reap great rewards through sponsored posts if they have a large enough following with this many eyes on their content. The question for today then becomes: How do we effectively grow our Instagram account in the age of algorithmic bias? Instagram expert and AI growth specialist Faisal Shafique help us answer this question utilizing his experience growing his @fact account to about 8M followers while also helping major, edgy brands like Fashion Nova to over 20M.

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This post is a collaboration with Dr. Augustine Fou, a seasoned digital marketer, who helps marketers audit their campaigns for ad fraud and provides alternative performance optimization solutions; and Jodi Masters-Gonzales, Research Director at Beacon Trust Network and a doctoral student in Pepperdine University’s Global Leadership and Change program, where her research intersects at data privacy & ethics, public policy, and the digital economy.

The ad industry has gone through a massive transformation since the advent of digital. This is a multi-billion dollar industry that started out as a way for businesses to bring more market visibility to products and services more effectively, while evolving features that would allow advertisers to garner valuable insights about their customers and prospects. Fast-forward 20 years later and the promise of better ad performance and delivery of the right customers, has also created and enabled a rampant environment of massive data sharing, more invasive personal targeting and higher incidences of consumer manipulation than ever before. It has evolved over time, underneath the noses of business and industry, with benefits realized by a relative few. How did we get here? More importantly, can we curb the path of a burgeoning industry to truly protect people’s data rights?

There was a time when advertising inventory was finite. Long before digital, buying impressions was primarily done through offline publications, television and radio. Premium slots commanded higher CPM (cost per thousand) rates to obtain the most coveted consumer attention. The big advertisers with the deepest pockets largely benefitted from this space by commanding the largest reach.

The subtle whirring of a battery-powered motor, the crunch of dried grass and leaves, and the whizzing of wind are all you will hear from the 2nd/14th Light Horse Regiment of Australia’s Queensland Mounted Infantry as its soldiers rush through the brush on stealthy e-bikes.

The e-bikes are being trialed to see if they can provide a worthy option for speedy, silent, and safe on-the-ground reconnaissance.

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Using machine learning, a computer model can teach itself to smell in just a few minutes. When it does, researchers have found, it builds a neural network that closely mimics the olfactory circuits that animal brains use to process odors.

Animals from fruit flies to humans all use essentially the same strategy to process olfactory information in the brain. But neuroscientists who trained an artificial neural network to take on a simple odor classification task were surprised to see it replicate biology’s strategy so faithfully.

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When asked to classify odors, artificial neural networks adopt a structure that closely resembles that of the brain’s olfactory circuitry.