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Extinct Snakes Lead to Better Fakes

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Flickr user sdbeazley

Some seemingly dangerous animals are really just sheep in wolves’ clothing. They’re harmless, but by imitating the appearance and warning signals that dangerous animals use to advertise their defenses (like toxins or painful stings), they fool predators into thinking they’re tough guys, too. 

Take the robber flies, for example. Some members of the family imitate the black and yellow striping of bumblebees and wasps, while others sport orange wings to look like tarantula hawks. Meanwhile, the non-venomous scarlet kingsnake (above) copies the pattern of black, red, and yellow bands worn by its neighbor, the coral snake, one of the most potently venomous snakes in North America.

How closely a mimic imitates its model often depends on how many of the models there are. Think of it like this, says evolutionary ecologist David Pfennig, who’s been studying mimicry in snakes for the last 15 years at the University of North Carolina: Say there’s a population of mimics that’s surrounded by lots of deadly models. The predators in the area are under strong selection to avoid the model (which they’re not doing actively—it’s a preference that’s innate, and not learned, with natural selection favoring traits and genes that help predators detect and avoid the prey’s warning signals) and its lookalikes because the chances of encountering the model are very high. Here, even poor mimics can get by with a less than perfect resemblance. 

If the models are rare compared to the mimics, though, and predators are less likely to encounter them, then the selection to avoid both model and mimic is more relaxed. In this case, trying to eat a crude mimic is less risky, which drives precision in the pretenders. 

But what happens to a mimic when its model disappears completely? Pfennig had the perfect opportunity to find out. In the North Carolina Sandhills, a thousand square miles or so of sandy hills and pine tree-dotted savanna, kingsnakes are pretty common, but coral snakes have always been considered rare. Today, they might not be there at all—researchers haven’t found any in the area since 1960. They’re locally extinct, leaving the kingsnake with a disguise that wouldn’t seem to do it much good. 

“When we embarked on this study, I thought that we would most likely find no change,” Pfennig said in an email. “After all, only about 50 years had transpired since coral snakes went extinct in the populations (that’s about 15 to 20 snake generations).” 

If there was going to be a change at all, Pfennig figured the mimics would become less accurate. In an earlier study, he’d found that kingsnakes’ patterns were closer to the corals’ in areas where they lived alongside each other, but not as good in places where there weren’t any coral snakes. 

The local predators avoided the mimics in the former areas, but not the latter. If mimicry breaks down in locations where the model is gone, Pfennig says, he expected something similar during times when it's absent, like after extinction. 

But that’s not what he and his grad student Chris Akcali found in the Sandhills. When they compared kingsnake specimens that had been collected between the 1970s and 2010s with preserved specimens of pre-extinction coral snakes and coral snakes still living in Florida, Pfennig said, “we witnessed the evolution of more refined mimicry.” Contrary to the scientists’ expectations, the Sandhill kingsnakes actually looked more and more like coral snakes as half a century passed without the models around. 

Since coral snakes were rare in the Sandhills before they went extinct there, there was already strong selection for precise mimicry in the kingsnakes. Pfennig and Akcali think that things kept moving in that direction because too few generations of predators have passed to reverse their avoidance of the deadly snakes and anything that looks a lot like them. 

“Somewhat paradoxically, selection imposed on mimics by predators can generate an evolutionary momentum that continues to favor more precise mimicry,” Pfennig said. “Even after the dangerous model has gone extinct.”

That momentum won’t last though, and the researchers expect the kingsnakes’ mimicry will eventually get less accurate. The biggest driver of that will probably be how desperate predators are to find food. If times get tough and animals becomes more willing to attack mimics, then there’s less pressure on the snakes to keep up the charade. On the other hand, if the snakes or their predators move back and forth between the Sandhills and areas where coral snakes are still present, that could bring in genes that have to do with avoiding mimics in the predators and/or genes for good mimicry in the snakes, which might let the mimicry linger. 

For now, the kingsnakes do a very good impression of the long-gone corals. Good enough that Pfennig says it caught him a little off guard. “Keep in mind that what makes a scarlet kingsnake look like a coral snake is a complex array of pattern elements: width of rings and the amount of red, black and yellow in each ring,” he said. “That you could get noticeable refinement of such a complex trait evolving in only a few dozen generations was surprising to me. It’s always exciting in science when you get results that you did not expect.”

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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]