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What Would Mars Have Looked Like Covered in Water?

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The western hemisphere of Mars, with the volcano Olympus Mons on the horizon. Photo courtesy Kevin Gill.

In September, NASA announced that the Curiosity rover found remnants of an ancient stream bed on Mars—evidence that our red neighbor was, at one point, a blue planet covered in water. Now, Kevin Gill, a software engineer, has given us a vision of what a watery Mars might have looked like.

According to Smithsonian's Smart News blog, Gill used elevation measurements based on the observations of NASA's Mars Reconnaissance Orbiter to create his vision. But he also took artistic liberties with his creation by exaggerating the topographic features approximately 10 times, choosing the height of the atmosphere and its clouds, determining a consistent sea level, and picking what areas would be covered by forest and desert. "I tried to envision how the land would appear given certain features or the effects of likely atmospheric climate," the engineer writes on his Google+ page. "For example, I didn’t see much green taking hold within the area of Olympus Mons and the surrounding volcanoes, both due to the volcanic activity and the proximity to the equator (thus a more tropical climate)."

To create the deserts, Gill used textures from the Sahara and the sands in Australia, and based the tropical and subtropical greens on the rainforests in South America and Africa. "As the terrain gets higher or lower in latitude I added darker flora along with tundra and glacial ice," he writes. "These northern and southern areas textures are largely taken from around northern Russia."


Photo courtesy Kevin Gill.

Gill hopes that his blue marble version of Mars will trigger the imagination, even if it isn't a totally scientific vision.

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iStock // Ekaterina Minaeva
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technology
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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iStock
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Health
One Bite From This Tick Can Make You Allergic to Meat
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iStock

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]

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