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How Did the States in the USA Get Their Names? (Part III)

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Reader Adam from Fairfax, Virginia, wrote in to ask, "How did the US states get their names?" This week, we're tackling the origins and meaning of the names 10 states at a time. Here's Massachusetts through New Jersey. (Be sure to also check out Monday's post on Alabama through Georgia and Tuesday's post on Hawaii through Maryland.)

Massachusetts

The Commonwealth of Massachusetts and the Massachusetts Bay Colony that preceded it were named after the area's indigenous people, the Massachusett. The tribe's name translates to "near the great hill," referring to the Blue Hills southwest of Boston. An alternate form of the tribe's name, the Moswetuset ("hill shaped like an arrowhead"), refers to the Moswetuset Hummock, an arrow-shaped mound in Quincy, MA.

Michigan

The state takes its name from Lake Michigan. Michigan is a French derivative of the Ojibwa word misshikama (mish-ih-GAH-muh), which translates to "big lake," "large lake" or "large water."

Minnesota

Minnesota is derived from the Dakota tribe's name for the Minnesota River, mnisota (mni "water" + sota "cloudy, muddy;" sometimes translated to the more poetic "sky-tinted water"). The English language doesn't really dig words beginning with mn (you'll find only one, mnemonic), so early settlers in the region added some i's and produced a mini sound that they wrote as "mine." The city of Minneapolis combines mni with the Greek polis, or "city."

Mississippi

The state is named for the Mississippi River. You may have heard that mississippi means "the Father of Waters" and you may have heard that from no less a source than novelist James Fenimore Cooper or President Abraham Lincoln (who wrote in a letter after the Civil War, "the Father of Waters again goes unvexed to the sea"). I hate to pee on Honest Abe's parade, but the word, a French derivation of the Ojibwa messipi (alternately misi-sipi or misi-ziibi) actually means "big river." It may not sound as dramatic as Lincoln's preferred translation, but whatever the meaning, the name caught on. As French explorers took the name down the river with them to the delta, it was adopted by local Indian tribes and replaced their own names, and the earlier Spanish explorers' names, for the river.

Missouri

The state and the Missouri River are both named after the Missouri people, a southern Siouan tribe that lived along the river. Missouri comes from an Illinois language reference to the tribe, ouemessourita, which has been translated as "those who have dugout canoes," "wooden canoe people" or "he of the big canoe."

Montana

Montana is a variation of the Spanish montaña, or "mountain," a name applied because of its numerous mountain ranges (3,510 mountain peaks, total). Who first used the name, and when, is unknown.

Nebraska

Nebraska comes from the archaic Otoe Indian words Ñí Brásge (in contemporary Otoe, it would be Ñí Bráhge), meaning "flat water." The words refer to the Platte River, which flows across the Cornhusker State.

Nevada

The state's name is the Spanish word for "snowfall" and refers to the Sierra Nevada ("snow-covered mountains") mountain range. The non-Nevadan pronunciation of the name "neh-vah-dah" (long A) differs from the local pronunciation "nuh-vae-duh" (short A) and is said to annoy Nevadans endlessly.

New Hampshire

John Mason named the area he received in a land grant after the English county of Hampshire, where he had lived for several years as a child. Mason invested heavily in the clearing of land and building of houses in New Hampshire, but died, in England, before ever venturing to the new world to see his property.

New Jersey

New Jersey was named for Jersey, the largest of the British Channel Islands, by its founders Sir John Berkeley and Sir George Carteret. Carteret was born on Jersey and served as its Lieutenant Governor for several years.

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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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