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Little-Known Second Verses of 10 Children's Songs

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Either I had a really short attention span as a kid and never made it past the first verse of a song (which is entirely possible), or there are some obscure lyrics to the songs we all know and love. Here are a few of them.

1. I'm a Little Teapot.
"I'm a clever teapot,
Yes it's true
Here let me show you
What I can do
I can change my handle
And my spout
Just tip me over and pour me out!"

2. Do Your Ears Hang Low? I'm impressed that a children's song contains the word "semaphore."

Do your ears hang high?
Do they reach up to the sky?
Do they droop when they are wet?
Do they stiffen when they're dry?
Can you semaphore your neighbour with a minimum of labour?
Do your ears hang high?

3. My Bonnie Lies Over the Ocean involves terrifying nightmares:

Last night as I lay on my pillow
Last night as I lay on my bed
Last night as I lay on my pillow
I dreamed that my Bonnie was dead

4. Oh My Darling Clementine. I didn't know anything beyond the "Oh my darling" chorus, but there's a whole little tale that goes along with the tragic Clementine. It goes like this (I'm leaving out the chorus, though):

In a cavern, in a canyon,
Excavating for a mine
Dwelt a miner forty niner,
And his daughter Clementine
Light she was and like a fairy,
And her shoes were number nine,
Wearing boxes, without topses,
Sandals were for Clementine.
Drove she ducklings to the water
Ev'ry morning just at nine,
Hit her foot against a splinter,
Fell into the foaming brine.
Ruby lips above the water,
Blowing bubbles, soft and fine,
But, alas, I was no swimmer,
So I lost my Clementine.
How I missed her! How I missed her,
How I missed my Clementine,
But I kissed her little sister,
I forgot my Clementine.

5. Alouette. This one isn't a lost verse "“ it's more that I had no idea what I was really singing about all of those years: bird dismemberment.

Alouette, gentille Alouette
(Skylark, nice skylark)
Alouette, je te plumerai
(Skylark, I shall pluck you)
Je te plumerai la tête
(I shall pluck your head)
(Je te plumerai la tête)
(I shall pluck your head)
Et la tête
(And your head)
(Et la tête)
(And your head)

The next verses include telling the captive bird that after his head, his beak, neck, back, wings, feet and tail will follow. Yikes!

6. Bingo. The earliest recorded version from 1888 adds two verses after the one that spells out the famous farmer's dog's name. They went like this:

Thys Franklyn, syrs, he brewed goode ayle,
And he called it Rare good Styngo!
S, T, Y, N, G, O!
He call'd it Rare goode Styngo!

Nowe is notte thys a prettie song?
I thinke it is, bye Jyngo,
J wythe a Y—N, G, O—
I sweare yt is, bye Jyngo!

7. Twinkle, Twinkle, Little Star.

When the blazing sun is gone,
When he nothing shines upon,
Then you show your little light,
Twinkle, twinkle, all the night.

Then the traveller in the dark,
Thanks you for your tiny spark,
He could not see which way to go,
If you did not twinkle so.

In the dark blue sky you keep,
And often through my curtains peep,
For you never shut your eye,
Till the sun is in the sky.

As your bright and tiny spark,
Lights the traveller in the dark,—
Though I know not what you are,
Twinkle, twinkle, little star.

8. Baa Baa Black Sheep. If you feel the need to deplete the rest of the barnyard denizens of their precious goods after you've taken the sheep's wool, you certainly can:
"Cluck, cluck, red hen, have you any eggs?
Yes sir, yes sir, as many as your legs.
One for your breakfast and one for your lunch;
Come back tomorrow and I'll have another bunch.
Moo, moo brown cow, have you milk for me?
Yes sir, yes sir, as tasty as can be.
Churn it into butter, make it into cheese,
Freeze it into ice cream or drink it if you please.
Buzz, buzz busy bee, is your honey sweet?
Yes sir, yes sir, sweet enough to eat.
Honey on your muffin, honey on your cake,
Honey by the spoonful, as much as I can make."

9. A Tisket, A Tasket. You probably know about the green and yellow basket, and you might remember that the person singing the song dropped it. After that, the sordid tale goes like this:

I dropped it, I dropped it
Yes, On the way I dropped it
A little girlie picked it up
And put it in her pocket

She was truckin' on down the avenue,
Without a single thing to do
She was peck-peck-peckin all around
When she spied it on the ground

She took it she took it
my little yellow basket
And if she doesn't bring it back
I think that I shall die

(Was it brown?) no, no,no, no,
(Was it red?) no, no,no, no,
(Was it blue?) no, no,no, no,
Just a little yellow basket

10. London Bridge is Falling Down. This song goes on forever. Tired parents might be glad their kids only know the first verse. If you're a glutton for punishment, though, here's the rest:

Build it up with wood and clay,
Wood and clay, wood and clay,
Build it up with wood and clay,
My fair lady.

Wood and clay will wash away,
Wash away, wash away,
Wood and clay will wash away,
My fair lady.

Then you "build it up with bricks and mortar" and sing that verse. But "bricks and mortar will not stay, will not stay, will not stay."

This is followed by "build it up with iron and steel," but "iron and steel will bend and bow."

So then we get extravagant and decide to "build it up with silver and gold," and, obviously, "silver and gold will be stolen away."

There are no other materials available, apparently, so we're going to stick with the precious metals and "set a man to watch all night, watch all night, watch all night." The question then is, "Suppose the man should fall asleep, fall asleep, fall asleep?" and the answer is, "Give him a pipe to smoke all night, smoke all night, smoke all night."

So there you have the solution to every crumbling bridge in the world: build it with silver and gold, pay a guy to watch it and let him smoke so he stays awake for his shift. Sound good?

So tell me: how many of you know the extended versions of these songs, and how many of you are just as surprised as I was?

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iStock // Ekaterina Minaeva
technology
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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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Animals
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Scientists Think They Know How Whales Got So Big
May 24, 2017
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iStock

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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