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How To: Fuel Your Car With Thanksgiving Leftovers

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Question: What's greasy, grimy, and surprisingly useful?

Answer: Turkey guts"¦and a lot of other stuff, too. It just depends on how you process it.

If you're reading this, you're probably hip to the concept that Americans (and pretty much everybody else in world) have a bit of an oil addiction and that, unlike some things you could get yourself addicted to, the supplies aren't limitless. So, wouldn't it be great if we could make it ourselves? Produce oil just like the Earth does—through pressure and heat—only faster? No, we haven't been painting in an unventilated room again...

It turns out that DIY oil is not only possible, it's a reality. As you read this, a factory near Carthage, Missouri is turning tons of waste from a nearby turkey slaughterhouse into diesel fuel and fertilizer. How? A little thing called thermal depolymerization.

See, oil is made naturally when carbon (usually in the form of dead plants and animals) gets buried under tons of earth and is then smooshed and heated by the movement of techtonic plates. Needless to say, this takes a while. But, in 2003, a company called Changing World Technologies perfected a way to duplicate this process in a factory in a fraction of a fraction of the time—as little as 15 minutes in some cases. Better yet, because of the way the process works, it's far more energy efficient than any other available method of producing biofuel, yielding 100 British Thermal Units of energy for every 15 BTUs spent in production.

But wait, this gets better. Not only can thermal depolymerization turn turkey into black gold, it can do the same thing with just about any carbon-containing substance—from raw sewage, to old car tires, to cast-off computers. Annnnd, what doesn't get made into oil ends up as other handy products, such as the aforementioned fertilizer or useful industrial chemicals.

So why haven't you heard of this? Frankly, we have no idea. Part of the problem, though, is that when Congress drew up regulations to give biofuel-producing companies a tax break in 2005, they wrote the legislation in a way that excludes thermal depolymerization. This makes it difficult to get investors and to compete with the tax-break-advantaged. Nevertheless, we like thermal depolymerization—with every fiber of our gizmo-loving, tree-hugging being—so we're hoping that if we explain more about how this works, maybe you'll spread the gospel.

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YOU WILL NEED
Pressure
Heat
Some sort of carbon-based waste material

Step 1: Grind it up
Whatever you're starting with, from computer parts to turkey giblets, will need to be chopped and churned into a fine, grainy mess.

Step 2: Add Water
According to a May 2003 Discover magazine article, this is the step that makes Changing World Technology's version of thermal depolymerization unique. Other attempts to recreate the process tried to siphon water away from the waste. CWT figured out that if they add more, then they don't have to heat or pressurize the sludgy glop nearly as much as they would for dry materials—the water helps spread the effect of the heat more efficiently.
Step 3: Depressurize
By quickly pumping the heated, pressurized slop into a depressurization chamber, CWT makes most of the water instantly evaporate out, a necessary step that would take a lot longer and a lot more energy to do by boiling. If you're making oil from turkey, this is the point where powdery fertilizer, chock full of minerals from the bones, settles out.
Step 4: Keep it Hot, Hot, Hot
The remaining liquid is heated to about 900 degrees F and sent through a series of distillers that separate it into natural gas, two different qualities of oil, and powdered carbon. The gas is used to fuel the process and the rest goes up for sale. For about 200 tons of turkey bits, the whole shebang takes less than 24 hours.

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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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