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Drew J, Philipp C, Westneat MW (2013)

How Ancient Shark-Tooth Swords Uncovered Two Long-Lost Species

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Drew J, Philipp C, Westneat MW (2013)

By Chris Gayomali

Biologist Joshua Drew's surprise discovery began as many do: "I just wanted to... look at really cool stuff," he tells The Los Angeles Times. Drew, now a postdoctoral researcher at Columbia University, was with a few colleagues at the Field Museum of Natural History in Chicago scoping out a new exhibit — a collection of "badass" swords, knives, and lances once used by the inhabitants of the Central Pacific's Gilbert Islands 130 years ago to rip their enemies to shreds.

This particular arsenal wasn't pounded out of iron or steel, though. The 124 flesh-tearing weapons on display had a more biological origin, and were carved out of wood, with each blade edge carefully outfitted with rows of dagger-like shark teeth. 

Drew was admiring the pieces when he noticed something strange: A few of the teeth appeared to belong to dusky and spottail sharks, which, oddly, aren't typically found near the Gilbert Isles. How could he tell, you might ask? Well, he was in a natural history museum, and could easily look up fossil records to confirm his suspicions.

"Shape, serration patterns, and other features of shark teeth were enough for researchers to identify the species," says LiveScience.

Using field guides and the museum's collections of shark jaws, the researchers identified teeth from eight species of shark on 122 weapons and teeth collections from the Gilbert Islands. The most common of those species was the silvertip shark (C. albimarginatus), whose teeth graced 34 weapons. Gilbert Islands weapon-makers also used teeth from silky sharks, oceanic whitetip sharks, tiger sharks, blue sharks, and hammerheads. [Live Science]

Yet, a deep-dive through history revealed no evidence that the dusky and spottail sharks had ever lived in Gilbert Island's reefs. While trading with other far-away cultures could explain how the teeth got there, the likelier answer is one we've already heard before:

"Probably, they were fished out," says Drew. Although it's not clear why the sharks disappeared,says Ed Yong at National Geographic — "people were hacking off shark fins in the Gilbert Islands as far back as 1910 and by the 1950s, around 3,000 kilograms of fins were being shipped from the islands every year." It's become so bad that some conservationists estimate that 100 million sharks are killed worldwide every year

After publishing their findings this month in the journal PLoS One, Drew and his team hope that the discovery of a "shadow biodiversity" along the Gilbert Islands' waters will aid conservation efforts for marine animals that have been over-fished for decades:

Given the importance of these species to the ecology of the Gilbert Island reefs and to the culture of the Gilbertese people, documenting these shifts in baseline fauna represents an important step toward restoring the vivid splendor of both ecological and cultural diversity. [PLoS One]

That's something worth sinking your teeth into.

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iStock // Ekaterina Minaeva
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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Nick Briggs/Comic Relief
What Happened to Jamie and Aurelia From Love Actually?
May 26, 2017
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Nick Briggs/Comic Relief

Fans of the romantic-comedy Love Actually recently got a bonus reunion in the form of Red Nose Day Actually, a short charity special that gave audiences a peek at where their favorite characters ended up almost 15 years later.

One of the most improbable pairings from the original film was between Jamie (Colin Firth) and Aurelia (Lúcia Moniz), who fell in love despite almost no shared vocabulary. Jamie is English, and Aurelia is Portuguese, and they know just enough of each other’s native tongues for Jamie to propose and Aurelia to accept.

A decade and a half on, they have both improved their knowledge of each other’s languages—if not perfectly, in Jamie’s case. But apparently, their love is much stronger than his grasp on Portuguese grammar, because they’ve got three bilingual kids and another on the way. (And still enjoy having important romantic moments in the car.)

In 2015, Love Actually script editor Emma Freud revealed via Twitter what happened between Karen and Harry (Emma Thompson and Alan Rickman, who passed away last year). Most of the other couples get happy endings in the short—even if Hugh Grant's character hasn't gotten any better at dancing.

[h/t TV Guide]