The Quick 10: Rain, Rain, Go Away

So it's been raining here in Des Moines pretty much since Friday night. On and off, but it's so random that you don't want to risk going outside for long periods of time because one second it's sunny and the next second dark clouds are rolling in and the sky opens up and spews forth torrential rains. We've been preoccupied with rain all weekend - my husband with the gutters and me with getting optimal sleep time (sleeping to the sound of rain is the best), so now I'm going to make you preoccupied with it too!

rain1. Seattle is known for being rainy, but it's by far not the rainiest town in the U.S. Washington isn't even the rainiest state in the U.S. or the rainiest state on the west coast! Portland, Oregon, is currently winning that battle with about 45 inches a year. Seattle gets an average of 37.1 inches. The state that gets drenched the most is technically Alaska with 160 inches every year, but if you're going for contiguous states, it's Alabama - Mobile spends nearly two months of every year pulling on galoshes and hoping they know where they left the umbrella.
2. Although you often see rain depicted as teardrop-shaped, it's anything but. What it looks like depends on how big it is. Small drops of rain are just about spherical, bigger ones are rounded on top and flat on the bottom, and really big ones are kind of parachute-shaped. Any bigger than about five mm and they fragment.

3. The biggest rain ever recorded happened in 2004 over Brazil and the Marshall Islands and clocked in at about 10 mm.

4. "Rain Rain, Go Away" has a few different versions. The one I know is "Rain, Rain, Go Away, come again another day." But "Raine raine goe to Spain: faire weather come againe," dates back to the 17th century; "Rain raine goe away,
Come againe a Saturday," was noted in a 1687 book by John Aubrey; and "Rain, rain, go away, Come again another day, Little Arthur wants to play," was published in the mid-19th century. Do you use a different version??

5. If you like the scent after a rain storm, what you really like the aroma of is petrichor. A bunch of plants secrete the oil during dry spells; the oil dries on the ground and rocks around it. When it rains, the drops hit the dry oil, which releases it into the air along with another compound called geosmin. But go ahead and say you love the smell of rain - I don't think anyone is going to correct you. And as a side note, I bet Dwight Schrute could tell you what geosmin is - it's also what makes beets taste earthy.

rain26. Lloró, a town in Chocó, Colombia, is the world's wettest place. Spanish speakers will get the joke - "llorar" means "to cry" in Spanish and is also sometimes used as a metaphor for rain. The town gets an average of 523.6 inches of rain every year - how crazy is that? It wouldn't be out of the ordinary for Lloró to get nearly 20 inches in a single day.
7. Bigger cities are more likely to get rain on Saturdays than small towns or rural areas. Why? In a word: people. All of the pollution humans generate with car exhaust and traffic and stuff like that collects during the week; by Saturday, the likelihood of rain is much higher than any other day of the week (as much as 22% in some places on the Eastern Seaboard).
8. The Mackintosh has been around since 1824. Charles Macintosh patented rubberized fabric in 1823 and his coats were being sold in stores just a year later. No one really knows why the "k" got added in - it seems to have just been an arbitrary marketing decision by a couple of writers somewhere down the line.

9. The maximum speed a raindrop can reach is 18 mph. At this point, the speed friction will make the raindrop break up into smaller particles, so it can't fall any faster.

10. A shower is officially classified as precipitation from a broken, bubble-like cloud. That's why they are so brief. If a shower lasts for more than 20 minutes, it's probably rain, which is precipitation from a layered cloud.

Maybe writing about rain will appease the gods and the sun will break through, but if the forecasters are right, we're in for more rain for the next week on and off. Booooo. So here's where you can help me - what do you do to salvage a rainy day? Looks like I'll have lots of opportunity to put your suggestions to the test over the next seven days or so!

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iStock // Ekaterina Minaeva
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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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]