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This Sixth-Grade Science Fair Project Shocked Scientists [Plus a Controversy]

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Florida has a lionfish problem. This menacing creature, which comes decorated with venomous spines, is an invasive species threatening the state’s habitat and wildlife. Until now, researchers thought the fish only thrived in the salty waters off Florida’s coasts. But a 6th grader’s science fair project proves otherwise.

"Scientists were doing plenty of tests on them, but they just always assumed they were in the ocean," 13-year-old Lauren Arrington told NPR. "So I was like, 'Well, hey guys, what about the river?'"

Yeah, guys, what about it? (Any 13-year-old who has the candor to address scientists with “hey guys” is already a winner in my book.) Lauren, a Florida native, wanted to know if the fish could survive in freshwater. So, with a little help from her ecologist dad, she set out for answers. She placed six different lionfish in six different tanks. Like any good scientist, Lauren was sure to have one control fish, which got to hang out in saltwater during the experiment. Over about a week, she slowly lowered the rest of the tanks’ salinity.

We express salinity by the amount of salt found in 1000 grams of water. So, one gram of salt equals a salinity of 1 parts per 1000. The average ocean salinity is 35 parts per 1000. Lauren lowered the salinity in her test tanks to 6 parts per 1000 and was surprised to find that her fish were still alive and well. She might have lowered the salinity further, but she didn’t want to kill the fish.

The lionfish has no natural predator on the Florida coast, so the fact that it can survive in freshwater means ecologists now know they must keep lionfish from migrating into the area’s rivers lest they do even more damage.

Lauren’s findings caught the eye of Craig Layman, an ecology professor at North Carolina State University. He replicated Lauren's results in a study published in the science journal Environmental Biology of Fishes. Lauren got a shout out in the acknowledgments.

UPDATE

But there’s a controversy brewing over whether Lauren’s project is authentic. A marine biologist named Zack Jud claims he published work back in 2011 [PDF] proving the lionfish’s tolerance for low salinity. His former supervisor, he says, is a close friend of Lauren’s family. On his Facebook page, Jud writes that "At this stage in my career, this type of national exposure would be invaluable...if only my name was included in the stories.”

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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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Nick Briggs/Comic Relief
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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]

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