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Look Up Tonight! It's the Super Hunter's Moon

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Sorry to say it, but your view of the Moon won't be as good as it was for ESA astronaut Tim Peake on March 28, 2016, when he captured this image of the Moon setting from the International Space Station. Image credit: ESA/NASA

Look up at the sky tonight, October 16, and you'll be treated not only to a full moon, but a supermoon. And not just any supermoon, but a Super Hunter's Moon!


Let's go over the fundamentals first. If nothing else, take away from this article the knowledge that the Moon's phases have nothing to do with the Earth's shadow. Yes, it kind of makes sense: the dark crescents, the predictability, and the orbits: one around the Earth, and both around the Sun. Shadows crossing orbs. But when the Earth's shadow crosses the Moon, you get a lunar eclipse.

The Moon's phases are a lot simpler than that. First, the Moon orbits the Earth every 29.5 days. You might have noticed that "moon" and "month" are similar words. That's not by accident. Moreover, the Moon is "tidally locked" with the Earth, which means from down here, we only see one side of the Moon, ever. Keep this in mind.

One half of the Moon is always fully illuminated by the Sun. As it creeps around the Earth over the course of a month, the illuminated area changes. When the Moon is generally opposite the Sun relative to the Earth (i.e. Sun-Earth-Moon), the side we can see is in full sunlight. It's a full moon. When the Moon is between the Sun and the Earth (Sun-Moon-Earth), the far side of the Moon—the half of it we never see—is in full illumination. In other words, the half we do see is receiving no sunlight at all. This is a new moon. (N.b. that there is no "dark side of the Moon." Every side of the Moon gets bathed in sunlight over the course of a revolution.)

The rest of the Moon's phases proceed from these fully lit or totally darkened states of visibility. As the Moon's orbit around the Earth takes it away from the Sun, it is said to be waxing, because from our point of view, the Moon is becoming increasingly full. After crossing the halfway point (the full moon), the visible Moon seems to darken. It is waning.


Not all full moons are created equal. Sometimes the full moon seems really, really big. Sometimes it seems weirdly small. This is because the Moon's orbit around the Earth is not a perfect circle, but rather, is elliptical. Sometimes it is closer to the Earth than other times. When it is close, it is said to be at perigee. When it is farthest away, it is at apogee. When the Moon is both at perigee and full, you get what is colloquially called a supermoon.

So what about this Hunter's Moon business? That is what some Native Americans called the full moon in October for reasons that must seem obvious. It provided extra light by which to hunt—a vital activity with winter's fast approach. (You might recall last month's harvest moon, whose name has the same rationale as this one: Gather your acorns before snow blankets the forest.)


Look up. Other things you'll see: tiny flickering dots that are stars, unless they're moving quickly, because those are likely airplanes or the International Space Station. If they're moving really, really fast, they're meteors. If you see a tiny stationary dot that doesn't flicker, it's probably a planet (or the tip of a cell phone tower). The super hunter's moon will make planet spotting more difficult. Uranus is at opposition this weekend and thus fully illuminated by the Sun from our point of view, but unless you're a first-rate astronomer with heavy duty hardware at your disposal, you won't be able to see it. The full moon above and light pollution below will join forces to wash it out. Even under the best conditions, it's really difficult to find. If you just vaguely point in the direction of the Moon and say, "See that dot? That's planet Uranus," people will probably believe you, though.

One more thing: Because we get a full moon this weekend, Halloween night will have a new moon. In other words, the night sky is going to be really dark: perfect conditions to test out your new clown costume and the response time of the local police department.

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iStock // Ekaterina Minaeva
Man Buys Two Metric Tons of LEGO Bricks; Sorts Them Via Machine Learning
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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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One Bite From This Tick Can Make You Allergic to Meat
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We like to believe that there’s no such thing as a bad organism, that every creature must have its place in the world. But ticks are really making that difficult. As if Lyme disease wasn't bad enough, scientists say some ticks carry a pathogen that causes a sudden and dangerous allergy to meat. Yes, meat.

The Lone Star tick (Amblyomma americanum) mostly looks like your average tick, with a tiny head and a big fat behind, except the adult female has a Texas-shaped spot on its back—thus the name.

Unlike other American ticks, the Lone Star feeds on humans at every stage of its life cycle. Even the larvae want our blood. You can’t get Lyme disease from the Lone Star tick, but you can get something even more mysterious: the inability to safely consume a bacon cheeseburger.

"The weird thing about [this reaction] is it can occur within three to 10 or 12 hours, so patients have no idea what prompted their allergic reactions," allergist Ronald Saff, of the Florida State University College of Medicine, told Business Insider.

What prompted them was STARI, or southern tick-associated rash illness. People with STARI may develop a circular rash like the one commonly seen in Lyme disease. They may feel achy, fatigued, and fevered. And their next meal could make them very, very sick.

Saff now sees at least one patient per week with STARI and a sensitivity to galactose-alpha-1, 3-galactose—more commonly known as alpha-gal—a sugar molecule found in mammal tissue like pork, beef, and lamb. Several hours after eating, patients’ immune systems overreact to alpha-gal, with symptoms ranging from an itchy rash to throat swelling.

Even worse, the more times a person is bitten, the more likely it becomes that they will develop this dangerous allergy.

The tick’s range currently covers the southern, eastern, and south-central U.S., but even that is changing. "We expect with warming temperatures, the tick is going to slowly make its way northward and westward and cause more problems than they're already causing," Saff said. We've already seen that occur with the deer ticks that cause Lyme disease, and 2017 is projected to be an especially bad year.

There’s so much we don’t understand about alpha-gal sensitivity. Scientists don’t know why it happens, how to treat it, or if it's permanent. All they can do is advise us to be vigilant and follow basic tick-avoidance practices.

[h/t Business Insider]