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9 Common Words That Come From Words for Heat

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From calm to ink, words we use that—surprisingly—can be traced back to words for heat.

1. calm

Calm is related to Old Spanish and Portuguese calma, which meant "heat of the day." That was the time when everything stopped for a while so people and animals could find some shade; the time when everything got quiet and calm. It comes from the Latin cauma for "burning heat." Now would be a good time to go find some shade and be still.

2. day

Day comes from Old English daeg, which is related to the words for "day" in other Germanic languages (dag in Swedish Danish, Tag German). Etymologists have traced it back to a root that also gave rise to Sanskrit dah, "to burn." It shows up with its "hot" sense in Lithuatian dagas, "hot season," and Old Prussian dagis, "summer." I think "burn season" may be more appropriate than "hot season" this summer.

3. bath

Bath can be traced back to an Old Germanic base bajo-, meaning "to foment," and related to the Latin fovere, meaning "to warm something up." It originally had the primary meaning of submersion in hot liquid and then came to be used for a bath in liquid of any temperature. Make that cold baths in cold Champagne for everyone!

4. breed

Breed is related to the Old Germanic root bro-, "to heat something up," like when birds warm their eggs to help them hatch. I hate to think of what new kinds of mold and bacteria might be breeding in garbage cans right now…

5. chafe

Chafe comes from the French chauffer, "to warm." It was used in English in the sense of warming things (this is how we get "chafing-dish"), but also for rubbing the limbs in order to warm them up, which led to the sense of "irritation through friction." What we need right now is a word for irritation through heat.

6. flagrant

Something that is flagrant is glaring and obvious, like … something that is on fire! It comes from the Latin flagrare, "to burn." Flagrant was indeed used to mean "fiery" for a time, but now the metaphorical meaning seems to be more popular. However, I will not take exception if you were to exclaim, "this day is positively flagrant!"

7. effervescence

Effervescense comes from the Latin exfeverscere, "to begin to boil," which is based on fervere, "to be hot." (The root that also gives us fervid, fervent, and fervor). The word has lost the hot part of its sense leaving us with just the bubbly part. Cold effervescent Champagne for everyone!

8. ink

Ink can be traced all the way back to the Greek form that also gave us "encaustic," meaning "to burn in," and referring to the process of burning wax paints onto objects to make the colors stay. Thankfully, we don't have to use fire to burn our words onto the page anymore, although my hot computer is kind of burning my wrists right now.

9. phlegm

For as long as it's been in English, "phlegm" has been associated with mucus and phlegmatic humor (from the theory of the 4 humors). The phlegmatic humor has always been thought of as the cold, clammy one, but the word "phlegm" relates back to the Ancient Greek phlegma, which referred to inflammation or the clamminess caused by being heated, which in turn relates back to the Ancient Greek for "burn" or "blaze." And about the image of burning phlegm, I have nothing more to say. Apologies.

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Man Buys Two Metric Tons of LEGO Bricks; Sorts Them Via Machine Learning
May 21, 2017
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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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Scientists Think They Know How Whales Got So Big
May 24, 2017
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It can be difficult to understand how enormous the blue whale—the largest animal to ever exist—really is. The mammal can measure up to 105 feet long, have a tongue that can weigh as much as an elephant, and have a massive, golf cart–sized heart powering a 200-ton frame. But while the blue whale might currently be the Andre the Giant of the sea, it wasn’t always so imposing.

For the majority of the 30 million years that baleen whales (the blue whale is one) have occupied the Earth, the mammals usually topped off at roughly 30 feet in length. It wasn’t until about 3 million years ago that the clade of whales experienced an evolutionary growth spurt, tripling in size. And scientists haven’t had any concrete idea why, Wired reports.

A study published in the journal Proceedings of the Royal Society B might help change that. Researchers examined fossil records and studied phylogenetic models (evolutionary relationships) among baleen whales, and found some evidence that climate change may have been the catalyst for turning the large animals into behemoths.

As the ice ages wore on and oceans were receiving nutrient-rich runoff, the whales encountered an increasing number of krill—the small, shrimp-like creatures that provided a food source—resulting from upwelling waters. The more they ate, the more they grew, and their bodies adapted over time. Their mouths grew larger and their fat stores increased, helping them to fuel longer migrations to additional food-enriched areas. Today blue whales eat up to four tons of krill every day.

If climate change set the ancestors of the blue whale on the path to its enormous size today, the study invites the question of what it might do to them in the future. Changes in ocean currents or temperature could alter the amount of available nutrients to whales, cutting off their food supply. With demand for whale oil in the 1900s having already dented their numbers, scientists are hoping that further shifts in their oceanic ecosystem won’t relegate them to history.

[h/t Wired]

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