This discovery really drives home the point of just how little we know about the universe. We wouldn’t expect a planet this heavy around such a low-mass star to exist.
A s the mathematician De La Soul famously stated, three is the magic number. But if physicist Richard Feynman is to be believed, that figure is off by a factor of about 400. For Feynman, you see, the “magic number” is around 1/137 – specifically, it’s 1/137.03599913.
Physicists know it as α, or the fine structure constant. “It has been a mystery ever since it was discovered,” Feynman wrote in his 1985 book QED: The Strange Theory of Light and Matter. “All good theoretical physicists put this number up on their wall and worry about it.”
It’s both incredibly mysterious and unbelievably important: a seemingly random, dimensionless number, which nevertheless holds the secret to life itself.
Explore Space Perspective as they showcase a version of Spaceship Neptune, set to take paying passengers on six-hour voyages up to 100,000 feet.
You’ve heard of hot Jupiters. You’ve heard of mini-Neptunes. You’ve heard of super-Earths. But have you heard of Eyeball Planets? Yep — planetary scientists think there might be a type of exoplanet out there that looks disturbingly like a giant eyeball. Just sitting there. Staring.
But it’s actually not as weird as it sounds — the appearance of these bodies has to do with tidal locking.
Tidal locking is when an orbiting body rotates at the same rate that it orbits. That means it always has one side facing the body it is orbiting, and the other side always facing away. The Moon, for instance, is tidally locked to Earth, that’s why we never see its far side from here.
Learn about the LVEM5 benchtop electron microscope with TEM, SEM and STEM modes. Nanoscale from your benchtop.
A world-first, non-invasive AI system can turn silent thoughts into text while only requiring users to wear a snug-fitting cap.
The Australian researchers who developed the technology, called DeWave, tested the process using data from more than two dozen subjects.
Participants read silently while wearing a cap that recorded their brain waves via electroencephalogram (EEG) and decoded them into text.
How do we solve the problem of job displacement? “The best way out is always through,” as Robert Frost said.
In the face of AI advancements, it’s time to double down on our uniquely human capabilities: imagination, anticipation, emotions and judgment—traits that machines cannot replicate.
AI has proven itself capable of tackling routine tasks within closed management systems but struggles when faced with open-ended problems requiring creativity and adaptability—a realm where humans reign supreme. Remember, there is more to work than simply executing tasks; there’s also vision-setting, team-building and innovation-driving. These areas are immune from automation because they require “the human touch.”
Transistor performs energy-efficient associative learning at room temperature.
An artistic interpretation of brain-like computing. Image by Xiaodong Yan/Northwestern University.
In theory, the immune system can recognize cancer cells as foreign and destroy them. In practice, this is often difficult, particularly after a tumor has become established in the body.
And even when immune cells, especially certain killer T cells, make it into a tumor, they face a hostile environment. This can include molecules that can disable T cells, low oxygen, and a lack of nutrients for energy. The end result is often a dysfunctional state known as T-cell exhaustion.
Now, a new study has confirmed the existence of yet another way that tumors can thwart T cells. In some tumors, a subset of cancer cells can act like a thief siphoning fuel from a car’s gas tank: they drain mitochondria —the tiny structures within cells that produce energy—from T cells and use them for their own energy needs.