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Scientists Say Greenland Sharks May Live 400 Years

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NOAA, Flickr // CC BY-2.0

Get ready to feel like a baby: There may be sharks alive today that are older than the United States. Like, much older. Researchers found a Greenland shark that’s around 392 years old—and 27 others with an average age of 272 years old. They published their findings today, August 11, in the journal Science. 

Young or old, Greenland sharks (Somniosus microcephalus, literally “tiny-headed sleeper”) are extraordinary creatures. They’re the second-largest carnivorous sharks in the world, reaching 2500 pounds. Their teeth are shaped and angled to remove plugs of flesh from their prey, and their own flesh is poisonous. 

Even so, Greenland sharks, like most sharks, present no risk to humans. They’re incredibly slow swimmers and live deep, deep down in the icy waters of the Arctic Ocean. These qualities make them both fascinating to scientists and tricky to track and study. And without data, it’s hard to argue that the sharks need protection.

Julius Nielsen

Previous studies had already found these sharks to have astonishingly long lives. The last estimate, based on a shark caught in 1952, concluded that they could live to be at least 200 years old. 

Science has come a long way since the 1950s, and researchers decided it was time to check again. Fortunately, they had access to a good number of Greenland sharks; unfortunately, that’s because those sharks had been accidentally caught in fishing nets and scientists’ long lines between 2010 and 2013. All 28 female sharks used in the study had been fatally injured by the time they landed onboard—some by other sharks, and some by fishing equipment—and so all were euthanized. After the sharks’ deaths, researchers measured each shark and took tissue samples from the lenses of its eyes. 

The scientists used radiocarbon dating on the samples to see if they could age the sharks. Once again, they had good data thanks to a bad situation—in this case, nuclear warfare. Scientists have known since the 1950s that nuclear bomb tests leave permanent molecular marks on sea creatures. Consequently, the appearance of bomb-related changes in an animal’s tissue can be seen as a sort of time stamp. But because these changes persist, even animals born after any given bomb can be marked by it if the animals they eat were alive during the test. 

By combining this information with the sharks’ body measurements, the scientists were able to estimate each animal’s approximate age. The youngest sharks sampled were less than 10 feet long and under 100 years old. These were mere pups for Greenland sharks; the data suggested that these animals don’t even reach sexual maturity until they’re around 150 years old. 

The oldest two sharks were 16 feet long apiece, and the scientists estimated their age at 335 (plus or minus 75 years) and 392 (plus or minus 120 years). Considering these averages, the researchers say, a conservative estimate of the shark’s longevity would put them at about 272 years old—still making them the oldest vertebrates on the planet. 

Given these astonishing findings and the threats posed to Greenland sharks by commercial fishing, the authors write, it’s time we start thinking about how to protect them.

Know of something you think we should cover? Email us at tips@mentalfloss.com.

 

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iStock // Ekaterina Minaeva
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Man Buys Two Metric Tons of LEGO Bricks; Sorts Them Via Machine Learning
May 21, 2017
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iStock // Ekaterina Minaeva

Jacques Mattheij made a small, but awesome, mistake. He went on eBay one evening and bid on a bunch of bulk LEGO brick auctions, then went to sleep. Upon waking, he discovered that he was the high bidder on many, and was now the proud owner of two tons of LEGO bricks. (This is about 4400 pounds.) He wrote, "[L]esson 1: if you win almost all bids you are bidding too high."

Mattheij had noticed that bulk, unsorted bricks sell for something like €10/kilogram, whereas sets are roughly €40/kg and rare parts go for up to €100/kg. Much of the value of the bricks is in their sorting. If he could reduce the entropy of these bins of unsorted bricks, he could make a tidy profit. While many people do this work by hand, the problem is enormous—just the kind of challenge for a computer. Mattheij writes:

There are 38000+ shapes and there are 100+ possible shades of color (you can roughly tell how old someone is by asking them what lego colors they remember from their youth).

In the following months, Mattheij built a proof-of-concept sorting system using, of course, LEGO. He broke the problem down into a series of sub-problems (including "feeding LEGO reliably from a hopper is surprisingly hard," one of those facts of nature that will stymie even the best system design). After tinkering with the prototype at length, he expanded the system to a surprisingly complex system of conveyer belts (powered by a home treadmill), various pieces of cabinetry, and "copious quantities of crazy glue."

Here's a video showing the current system running at low speed:

The key part of the system was running the bricks past a camera paired with a computer running a neural net-based image classifier. That allows the computer (when sufficiently trained on brick images) to recognize bricks and thus categorize them by color, shape, or other parameters. Remember that as bricks pass by, they can be in any orientation, can be dirty, can even be stuck to other pieces. So having a flexible software system is key to recognizing—in a fraction of a second—what a given brick is, in order to sort it out. When a match is found, a jet of compressed air pops the piece off the conveyer belt and into a waiting bin.

After much experimentation, Mattheij rewrote the software (several times in fact) to accomplish a variety of basic tasks. At its core, the system takes images from a webcam and feeds them to a neural network to do the classification. Of course, the neural net needs to be "trained" by showing it lots of images, and telling it what those images represent. Mattheij's breakthrough was allowing the machine to effectively train itself, with guidance: Running pieces through allows the system to take its own photos, make a guess, and build on that guess. As long as Mattheij corrects the incorrect guesses, he ends up with a decent (and self-reinforcing) corpus of training data. As the machine continues running, it can rack up more training, allowing it to recognize a broad variety of pieces on the fly.

Here's another video, focusing on how the pieces move on conveyer belts (running at slow speed so puny humans can follow). You can also see the air jets in action:

In an email interview, Mattheij told Mental Floss that the system currently sorts LEGO bricks into more than 50 categories. It can also be run in a color-sorting mode to bin the parts across 12 color groups. (Thus at present you'd likely do a two-pass sort on the bricks: once for shape, then a separate pass for color.) He continues to refine the system, with a focus on making its recognition abilities faster. At some point down the line, he plans to make the software portion open source. You're on your own as far as building conveyer belts, bins, and so forth.

Check out Mattheij's writeup in two parts for more information. It starts with an overview of the story, followed up with a deep dive on the software. He's also tweeting about the project (among other things). And if you look around a bit, you'll find bulk LEGO brick auctions online—it's definitely a thing!

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May 23, 2017
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