Science Friday - Earth May Once Have Had A Ring Like Saturn | An AI For Sand

Episode Date: September 20, 2024

The ring would have gradually fallen to Earth as meteorites, correlating to a spike of impacts seen in the geological record. Also, a new AI tool can judge whether sand came from a beach, a river, a glacial deposit, or a wind-blown dune.Earth May Once Have Had A Ring Like SaturnHundreds of millions of years ago, Earth may have looked quite different when viewed from space: Scientists propose it may have had a Saturn-like ring, made up of lots of smaller asteroids.The new paper, published in Earth and Planetary Science Letters, proposes that this ring formed around 466 million years ago. A major source of evidence is a band of impact craters near the equator. The researchers also posit the ring would have shaded this equatorial area, possibly changing global temperatures and creating an icehouse period.Ira speaks to Rachel Feltman, host of the Popular Science podcast “The Weirdest Thing I Learned This Week,” about this and other top science stories of the week, including how lizards use bubbles to “scuba dive” underwater, and ancient cave art that possibly shows a long-extinct species.An AI To Identify The Environment A Grain Of Sand Came FromIf you were given a bucket of sand and asked to determine where it came from, you’d probably have a hard time guessing if it was from a beach, a riverbank, the playground down the street, or a Saharan sand dune.There are experts who can make a guess at that sort of ID, using a categorization process that takes skill, a scanning electron microscope, and hours of time. Now, however, researchers report in the Proceedings of the National Academy of Sciences that they’ve developed an AI model that can quickly judge whether a sample of sand came from a beach, a river, a glacial deposit, or a wind-blown dune.That type of identification isn’t just of interest to geologists. Sand is one of the world’s most in-demand resources, second only to water in use. And different applications need different types of sand—for instance, making concrete and mortar requires angular sand for good adhesion and stability. These kinds of needs have given rise to illicit sand mining, sand theft, and sand smuggling. A way of rapidly identifying the origins of a sample of sand could be useful to investigators, or to companies seeking to ensure sustainability goals.Michael Hasson, a PhD candidate in Stanford’s Department of Earth and Planetary Sciences, joins SciFri’s Charles Bergquist to discuss the new SandAI, and the challenges of tracking grains of sand.Transcripts for each segment will be available after the show airs on sciencefriday.com. Subscribe to this podcast. Plus, to stay updated on all things science, sign up for Science Friday's newsletters.

Researchers built a new AI tool to sort grains of sand. Why? Partly to thwart sand bandits, of course. Something that the world is going to start having to grapple with more or more is where we get our sand from. It's Friday, September 20th, and this is Science Friday. I'm SciFRI producer Kathleen Davis. Though sand might seem super ordinary and common,

it's one of the most crucial resources in our modern world. second only in use to water. Coming up, we'll talk about a new computer model that can tell if sand is more likely to have come from a river, a glacier, an ocean beach, or a desert dune. And that could be extended to trace a bucket of sand to a specific location. But first, Ira Flato and guest Rachel Feldman round up some of the biggest science stories of the week. A new study in the journal Nature has found the black hole blasting a massive, jet that's 23 million light years long. That is quite long. Joining me to talk about this and other top science stories of the week is Rachel Feldman, host of the popular science podcast, the weirdest

thing I learned this week based in New York. Welcome back. Thanks for having me, Ira. All right, let's talk about this black hole. First of all, what is a black hole jet? Fill us in on that. Yeah. So in black holes of pretty much every size, something interesting can happen, around the inner edge of the accretion disc. Basically, a little bit of material that is getting pulled towards the black hole can suddenly just blast out through these jets that stream out in opposite directions. And they fire out particles at close to the speed of light. So they're super interesting, you know, parts of the black hole landscape. Wow. And we're talking about big numbers here, right? 23 million light years. Can you give us some way of digestive?

that number. I can. That is the equivalent of lining up 140 Milky Way galaxies back to back. So pretty big. And how did they detect this? Yeah, so they found this with the low frequency array or low far radio telescope. This is a European instrument. It's been doing a sky survey. And it's actually found more than 10,000 of these megastructures, though this is, of course, a pretty superlative one. But one thing that's really exciting is that Lofar is doing a sky survey, like I said, and they've only actually surveyed about an eighth of the sky so far. So, you know, it's possible they'll find one that's even bigger. Yeah. Wow. Okay. So how does this discovery change what we know about black holes? So I think there's still a lot of research to be done to figure out exactly what we can

learn from this object. But scientists are really excited because it's not just the biggest one we've seen. It's also quite old. It's 7.5 billion light years away, which means it's 6.3 billion years old. So it's from when the universe was like half of its current age. And they're really interested in seeing how these jets might have contributed to like the formation and development and shaping of early galaxies. So it's a really exciting avenue to go down. That is cool. Speaking of something else cool, something, another story about our planet, it turns out Earth used to look quite a bit different. It may have had a ring around it like Saturn. Yeah. So this theoretical ring, it would have formed 466 million years ago. And basically, you know, experts are saying a gigantic asteroid could

have been tugged apart by Earth's tidal forces and, you know, left behind all of this debris that formed a ring that, you know, for some amount of time, circled around Earth. Well, so we had like lots of tiny asteroids in the ring and what's the evidence for this? So the evidence is, it's really interesting because the researchers were trying to explain this period in Earth's history that was 485 million to 443 million years ago when we know that there were a lot of meteorite impacts. It was a really tumultuous time on Earth. So they decided to look at 21 impact craters from that time. And they were seeing that they were all really close to the Earth's equator. And that was just like statistically very unlikely. And they calculated

how unlikely. And they said it was the same probability as tossing a three-sided die 21 times and getting the same outcome all 21 times. So that made them think the more likely explanation was that the reason all these meteorites fell around the equator was that they were in orbit around the equator. So that's sort of how they reverse engineered this. And one interesting thing is that this was also a very cold period in Earth's history and a ring could have blocked enough sun to explain that cooling. So while we need to, more evidence to be, like, confident that Earth had this, like, little fashion accessory. It does kind of, like, neatly explain some weird things about that period.

Yeah, well, the ring went away by all the stuff falling to Earth, so that explains. Exactly, yeah. All right, one more space story before we come back to TerraFerma. And this is just as wild as your first. We're getting another moon, a mini moon for a couple of months? Tell us about this. Yeah, a mini moon. Don't tell the main moon.

It might get jealous. But yeah, occasionally something will get pulled into Earth's orbit. Obviously, lots of things are already in orbit because we put them there. Lots of things come close to Earth without actually formally orbiting us, you know, because they are just orbiting the sun as we do as well. But every once in a while something gets pulled into our gravity and circles around us for long enough that it's something called a mini moon. It's just a little temporary moon.

And scientists say we're getting another one from September 2,000. 29th to November 25th. It was spotted by the asteroid terrestrial impact last alert system. So, you know, those guys who are keeping an eye out for asteroids that get too close for comfort. And in tracking this one's orbit and, you know, determining its trajectory, they said, you know, it will make a sort of horseshoe orbit around Earth and then return to orbit around the sun. though it'll actually come back to orbit us again in 255. Wow. Is this an uncommon or a common thing to happen?

Because we've never heard about it. So we have had mini moons before. There was one that orbited Earth for a few years before leaving again in 2020. There was another object that became a mini moon of Earth in 1981 and 2022. And we'll come back again in 2015. So it's not something that happens every day, but it's not super uncommon. And, you know, a lot of these objects are really small. This one is too small for, you know, hobbyists to see in their backyard.

But people with larger telescopes will be able to spot it. So, you know, if people keep an eye out on, you know, NASA or their local university, they might be able to see some cool images of it. Just too bad. All right. Let's get back closer to Earth and about some, speaking of rock, some old rock art. A mysterious animal was discovered in South African Roe. rock art from a few hundred years ago? Why is this important? Yeah, so this is important because it's a great

reminder of sort of the stories we tell about natural history and how science works and who we give credit for discovering fossils and looking at them. Basically, we're looking at some rock art done by the San people of South Africa between 1821 and 1835. There are a bunch of figures painted, and this is a portion of it called the horned serpent panel. And one of the figures on it has sort of defied identification for a while. It's this very long-bodied animal. It has these tusks that turn downward. And it doesn't match any modern species that we know of in the area.

But researchers had noted that there's evidence that the Sond people collected fossils and incorporated them into their art. So now researchers are saying this kind of animal that is known to be very abundant and have a lot of well-preserved fossils in this area, the Karoo Basin of South Africa. These animals called Dicinidants, they are saying they're a really good match. And the reason that's interesting is that they went extinct long ago before the dinosaurs, but we know that there are a lot of well-preserved fossils of them in the area. And we also know that Western scientific descriptions of these animals didn't come out until 1845. So that's 10 years after the latest possible date of these cave paintings. So essentially, researchers are saying that these indigenous people were collecting fossils and creating illustrations of these long extinct animals before European scientists came and did the same. same. And it's just adding to this, you know, growing body of evidence that there was extensive

indigenous knowledge of paleontology that has been really poorly understood, particularly in this region of Africa, and that we have a lot to learn about what these people were learning before any colonial influence came in. That is fascinating. Fascinating. All right, let's talk about animals that exist today. And I'm looking at seabirds, new information about their beaks. Tell us, please, yeah. Well, so we already know that some birds like ducks use their beaks really similar to the way that we humans use our hands. They have a lot of sensitivity in parts of their beaks, and so they're able to have these very touch-sensitive areas that help them find food. But we don't really know how common this is, you know, in the larger world of birds.

And so researchers decided to look at this large and poorly studied group of seabirds that include. includes albatrosses and penguins. They're especially interested because so many of the birds in that group are endangered. And, you know, understanding how they look for food could be an important way to help conserve them. And when they looked at 361 modern bird species, they found out albatrosses and penguins do indeed have these, like, very dense sensory receptors and, you know, high concentrations of nerves in their beaks. So they're doing this tactile foraging that we didn't know that seabirds could do. That is cool.

All right. Let's stay with our animal theme today and talk about lizards, lizards making their own scuba diving gear from bubbles. Okay, you got my attention on this way. I absolutely love this one, Ira. So we've known for a while, or researchers have known, I didn't know this, researchers have known that these semi-aquatic lizards called water annals have this trick where they dive underwater to escape predators. One of the researchers said that these guys are like the chicken nuggets of the forest.

Everything wants to eat them. So they very frequently have to dive under the water to escape predators. And something that happens when they do that is that these little bubbles form on top of their heads. So we knew about the bubbles, but scientists weren't sure whether they had a function. And so in this very clever study, researchers basically put an emollient on the lizard's skin to make it less hydrophobic. so that air wouldn't stick to it, so the bubble wouldn't form. And so then they were able to compare how long the lizard stayed underwater with the bubbles and without. And they found that actually the bubble really helps them breathe underwater.

It's serving as like a little scuba helmet. And this is how they're able to stay underwater to avoid predators for, you know, 20 minutes or more. 20 minutes or more little scuba diving. That is terrific. Rachel, always happy to have you on the show. bring such great stuff with you. Thanks, Ira. Rachel Feltman, host of the popular science podcast, the weirdest thing I learned this week. She's based in New York. Science Friday's 33rd anniversary is coming up on Friday, November 8th, 2024. And to celebrate, we'd like you to help choose the programming

for our anniversary broadcast. Head to ScienceFriday.com slash 33 to learn more about how to donate and vote on your favorite sci-fri stories. If I gave you a bucket of sand and asked you to tell me where it came from, I'm guessing you'd have a hard time telling me if it was from a Saharan sand dune, an ocean beach, or a riverbank. There are experts who could make a guess at that sort of ID based on a process that takes skill, a scanning electron microscope, and hours of time.

But of course, now there's an AI for that. Joining me now is Michael Hassan. He's a PhD candidate in Stanford's Department of Earth and Planetary Sciences and lead author on a paper describing this new AI for Sand that was published this week in the proceedings of the National Academy of Sciences. Welcome to Science Friday. Hey, thank you so much for having me. It's great to be here. Great to have you. Walk me through this challenge I mentioned. I give you a bucket of sand. How would you start trying to ID it without your tool? Yeah, so in the past, it's basically

amounted to filling out a spreadsheet with about 30, 35 different features. And a human would go through each photo and make a checkmark next to each feature that was present. Things like whether the grain is angular, subangular, or rounded, the presence of arcuate steps, parallel striations or elongated depressions. And so at each step, the human is making this judgment call about very specific terms that have really big implications for where the sand actually comes from. So it's a hugely subjective process, and it takes a really long time. Is this something that a regular person could pull out a magnifying glass and see some

of this, or do you really need your scanning electron microscope to make this determination? Yeah, we really need a microscope to do this, and particularly the scanning electron microscope that is able to resolve these features that are less than a micron. Is there any kind of like standard for categorizing sand? Do sand people look at a sample and say, oh, that's clearly a Josephson type 2A? No, it really all exists along a spectrum. And so using some statistical analyses, we can tell you if it's more like, one environment or another, but we can't really give you hard specific answers about where it exactly comes from.

So forgive me for asking this, but is there really a huge need for rapid, accurate sand identification? Yeah, that's a totally fair question. Outside of fundamental sciences like geology, georechaeology, something that the world is going to start having to grapple with more or more is where we get our sand from. Sand sourcing is this really critical problem because after water, it's the second most important raw material in the world. And anything that we build that's made out of concrete is reliant on sand.

And not just any sand, it has to be angular sand so that the grains lock together and form a structurally sound material. And so what that's led to is a lot of illegal mining of sand, especially in places like Southeast Asia, they're developing very rapidly. They're often companies that set up on a riverbank and they just start removing sediment. And so if you're a construction company that's trying to make sure you're sourcing your sand responsibly, using our tool is a way that you're, you can confirm whether your supplier is being accurate about what they're telling you and where that sand is coming from. Yeah. So break it down for me. How structurally is sand from, say, a beach dune different from sand on a Saharan Desert dune to an expert? Different environments can produce very similar textures. So it's really helpful to look at these in ensemble. And so when a human has been doing this in the past, they've taken the sample of, say, 100 grand. And they've said, okay, on average, this sample is a little bit more round. than another. And if it's a little bit more round, maybe that means it was moved by wind instead of

water because when grains collide in the air, there's less of a viscous fluid to soften the impact between them. And so when they collide in the air, it just break off and the grains become more round. But it's a non-unique process. And so that's why we were really excited to apply machine learning to this, to try to capture these patterns that are really difficult to get at from just a human analysis. So now you have this AI tool that you've trained on thousands of known samples of sand. Can it do this task better? Yeah. So this tool that we've developed doesn't just take one sample and condense it down to a single result.

So historically, we've taken the sample of, say, 100 sand grains. And that sample is more or less beach. That would be the answer that you could get from it. With this new tool, we can get an answer for every single sand grain, which lets us do a much better job of fingerprinting. individual sites and telling more complex stories of whole samples. And so one really neat example of this was from a sample that we used to test the model from the bottom of the Mississippi River. So the Mississippi River is about 2,000 miles long. And we sampled from very end of it. And rather than showing an entirely river-dominated signature, the sample was about 50% river and 50% windblown sand.

And so at first, that might seem a little bit puzzling, but it's telling you. this really interesting story. And the stories that way upstream, the banks of the Mississippi River are made out of wind-blown sediment that was deposited around the last ice aid. And so just using our tool, we can start to piece together the story of a modern river moving across this bed of ancient wind-blown sand to get this really interesting picture of how that part of the world has evolved just by looking at a few grains of sand. So if you come up with this answer that's like this is 50% wind-blown, 50% river, does that give you like a fingerprint of the Mississippi? If you come up,

up with those numbers, do you say this is probably Mississippi River sand as opposed to some other place? Right now we're working with probably. We haven't compiled that whole data set of what different major rivers, let's say, around the world would produce in terms of the distribution of different environments that our model would predict. But that's likely a really good signature for individual sites that we could use going forward. Huh. I mean, if you were able to give it enough samples of very specific rivers. Could you fine-tune this model to be even more specific, like picking out one river environment versus another? Yeah, absolutely. So that brings up this really important point, kind of within the broader machine learning world, which is the idea of

transfer learning. And transfer learning is this idea that a model that's trained to do one task well can likely be fine-tuned to do another similar task even better than it would be able to do if it were just starting from scratch. And so what we've achieved now is we have a model that sort of knows how to work with sand. And if we were to take this model and compile a different set of data where we know exactly what site the sample comes from rather than what environment it's made up of, we could train the model to distinguish between different rivers, let's say, and it would be expected to perform much better than if we were just training the model from scratch.

I mean, you mentioned sand forensics in the context of, you know, construction companies, but is there any possible use here for like regular police forensics or, I don't know, archaeological exploration or something like that? It's something that people have looked into for regular police forensics in terms of using it to test a sample that was on a murder suspect shoe and seeing if it confirms or refutes their alibi. Geo archaeology is a context that we're really excited for this to be used in, too, because this is a new tool for contextualizing environments when we have really limited data available. One really neat example that we found had to do with taking a core through an archaeological

site with the goal of contextualizing where artifacts were coming from. So where were people living? Was this a river where they living in a desert? And that's really hard to do, especially when there's no real rock outcrop that geologists could look at. And so when you take a core to minimize the destruction of the site, you also lose all the context. for where that sediment is coming from. And so having a tool like this that can provide some environmental information without any context can be really critical in some situations. So where do you go from here with this?

What would be the next step in this research? So we've publicized the model so that it's online for anybody to use freely. And we're hoping that as more and more people use it, we will understand better the instances where it works and instances where it doesn't. We've tested it to know that it works. to know that it works quite well in as much data as we have available. But given the natural variability of the world, there will almost certainly be places where it fails. And knowing about those will help us tweak the model and come up with a new version of it

that will work in an even wider variety of settings. Very cool. Michael Hassan is a PhD candidate in Stanford's Department of Earth and Planetary Sciences. Thanks so much for taking time to talk with me today. Absolutely. Thank you so much for having me on. And that's it for today. On Monday, Ira talks with U.S. Surgeon General Vivek Murthy about his latest advisory on parental well-being and mental health.

And his decision to declare gun violence a public health crisis. Lots of folks help make the show happen, including Diana Plasker. Beth Ramney. Danielle Johnson. Santiago Flores. And many more. Wishing you a great weekend. I'm Kathleen Davis.

Thanks for listening.