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A Spoonful of Wheaties Facts

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Maybe because it doesn't get much competition from Little Chocolate Donuts (the donuts of champions), but more probably because of its genius marketing, Wheaties has been a breakfast staple for little athletes everywhere. Let's take a look at look back at some of the stories that make this cereal so great.

1. They were almost called Nutties

Wheaties were invented when a dietician working for the Washburn Crosby Company was preparing bran gruel in 1924 and spilled some onto the hot stove top. The droplets sizzled and then hardened into tiny "flakes." The clumsy cook found them to be far tastier than standard gruel. He informed his superiors of his discovery, and 36 recipe variations later the company developed a wheat flake that was strong enough to withstand packaging and shipping. The name "Wheaties" was chosen via a company-wide contest, beating out other suggestions such as "Nutties" and "Gold Medal Wheat Flakes."

2. It's the Cereal that got Ronald Reagan to Hollywood

aron.jpgIn 1937, General Mills sponsored a contest in which the public voted for their favorite Wheaties announcer (the voice that intoned Wheaties commercials during ballgames). The winner was a sportscaster from Des Moines, Iowa, named Ronald Reagan (who called the play-by-play using his nickname "Dutch"), and his prize was an all-expense trip to the Cubs' spring training camp in California. While there, he managed to get a screen test at Warner Brothers, and we hear that he eventually got involved in politics"¦

3. Cover Models: A Few Famous Firsts

Picture 34.pngIn its early years, Wheaties put photos of famous sports figures on the side panels or back of their boxes. Lou Gehrig was the first athlete to appear on the box, and the first female was not a sportswoman, per se, but an aviatrix "“ Elinor Smith. Wheaties didn't put a woman on the front of their box until 1984 (over 30 years after the first male athlete appeared in that spot), when gymnast Mary Lou Retton graced the cover. The first athlete to appear on the front of the box was decathlete Bob Richards in 1958. Believe it or not, of all the sports represented on the Wheaties box, football did not make the front cover until 1986 when Walter Payton added his own brand of sweetness to the mix.

4. Where the Slogan Came from

One of history's most enduring cereal box slogans was conceived on the spur of the moment. When Wheaties first started sponsoring radio broadcasts of Minneapolis Millers baseball games in 1933, their agreement included a large sign at the ballpark promoting the cereal. When asked what he wanted the sign to say, an ad exec for Wheaties thought for a moment then blurted out, "The breakfast of champions." The company eventually sponsored various baseball teams across the country, and testimonials by famous athletes became a staple of Wheaties radio commercials.

5. Fan Favorites

Wheaties_Jordan.jpgAs part of their 75th anniversary celebration in 1999, Wheaties asked the public to vote for their favorite "Wheaties Champion." The final tally:
10.  1980 U.S. Men's Olympic Hockey Team
9.    Jackie Robinson
8.    John Elway
7.    Walter Payton
6.    Cal Ripken, Jr.
5.    Tiger Woods
4.    Mary Lou Retton
3.    Babe Ruth
2.    Lou Gehrig
1.    Michael Jordan

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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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Stephen Missal
crime
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New Evidence Emerges in Norway’s Most Famous Unsolved Murder Case
May 22, 2017
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A 2016 sketch by a forensic artist of the Isdal Woman
Stephen Missal

For almost 50 years, Norwegian investigators have been baffled by the case of the “Isdal Woman,” whose burned corpse was found in a valley outside the city of Bergen in 1970. Most of her face and hair had been burned off and the labels in her clothes had been removed. The police investigation eventually led to a pair of suitcases stuffed with wigs and the discovery that the woman had stayed at numerous hotels around Norway under different aliases. Still, the police eventually ruled it a suicide.

Almost five decades later, the Norwegian public broadcaster NRK has launched a new investigation into the case, working with police to help track down her identity. And it is already yielding results. The BBC reports that forensic analysis of the woman’s teeth show that she was from a region along the French-German border.

In 1970, hikers discovered the Isdal Woman’s body, burned and lying on a remote slope surrounded by an umbrella, melted plastic bottles, what may have been a passport cover, and more. Her clothes and possessions were scraped clean of any kind of identifying marks or labels. Later, the police found that she left two suitcases at the Bergen train station, containing sunglasses with her fingerprints on the lenses, a hairbrush, a prescription bottle of eczema cream, several wigs, and glasses with clear lenses. Again, all labels and other identifying marks had been removed, even from the prescription cream. A notepad found inside was filled with handwritten letters that looked like a code. A shopping bag led police to a shoe store, where, finally, an employee remembered selling rubber boots just like the ones found on the woman’s body.

Eventually, the police discovered that she had stayed in different hotels all over the country under different names, which would have required passports under several different aliases. This strongly suggests that she was a spy. Though she was both burned alive and had a stomach full of undigested sleeping pills, the police eventually ruled the death a suicide, unable to track down any evidence that they could tie to her murder.

But some of the forensic data that can help solve her case still exists. The Isdal Woman’s jaw was preserved in a forensic archive, allowing researchers from the University of Canberra in Australia to use isotopic analysis to figure out where she came from, based on the chemical traces left on her teeth while she was growing up. It’s the first time this technique has been used in a Norwegian criminal investigation.

The isotopic analysis was so effective that the researchers can tell that she probably grew up in eastern or central Europe, then moved west toward France during her adolescence, possibly just before or during World War II. Previous studies of her handwriting have indicated that she learned to write in France or in another French-speaking country.

Narrowing down the woman’s origins to such a specific region could help find someone who knew her, or reports of missing women who matched her description. The case is still a long way from solved, but the search is now much narrower than it had been in the mystery's long history.

[h/t BBC]

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