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10 (un)American Icons

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When you think of 7-Eleven, the Chrysler Building, and Budweiser, what country comes to mind? If you said Japan, Abu Dhabi, and Belgium, then no need to read on. But if such news comes as a shock, keep reading to learn about ten un-American Icons this country holds dear.

1. Anheuser-Busch, Inc.
You've likely seen the Anheuser-Busch commercials that were shown during the Olympics. You know, the ones that are oozing with everything American "“ football, tailgating, the Statue of Liberty, riding motorcycles, playing in a garage band, and, of course, a fat slice of apple pie. In case you didn't get the hint, they're reminding you that their All American Ale is still All American. But it's not American at all! Earlier this year, Anheuser Busch Inc was bought by InBev, the Belgian brewer. The deal, soon to close, will make the new combined company "Anheuser Busch InBev" the largest beer company in the world.

2. The Chrysler Building
In July, the Abu Dhabi Investment Council's sovereign wealth fund bought a 90% stake in the Chrysler building for an estimated $800 million. The building management will remain under Tishman Speyer Properties, who owns the remaining 10%. Prior to Abu Dhabi's purchase, the majority (75%) of the building was owned by TMW, a German real estate fund.

3. The Plaza Hotel
The Plaza Hotel, near Central Park, is co-owned by Prince bin Alwaleed bin Talal and Israeli billionaire Yitzhak Tshuva's El-Ad Group. The hotel's ownership passed through the hands of the Hiltons and the Trumps until Trump sold to the partnership for $325 million in 1995.

4. Essex House in Manhattan
This landmark hotel was bought by the Dubai Investment Group in 2005 and is under management by the Dubai based hospitality group, Jumeriah. Jumeriah operates the only 7-star hotel in the world—the Burj Al Arab in the UAE.

5. 7-Eleven
Yes, 7-Eleven is a subsidiary of the Japanese company Seven & I Holdings. The company faced financial difficulties in the 80s, and was rescued by one of the franchisees in Japan. In the 90s, Seven & I bid for and received a controlling share of the company.

6. The Chicago Skyway
In 2005, the city of Chicago sold a 99-year lease on the eight-mile Chicago Skyway for $1.83 billion to the Skyway Concession Company, which is jointly owned by the Macquarie Infrastructure Group of Sydney, Australia, and the Cintra Concesiones de Infraestructuras de Transporte of Madrid, Spain. Chicago used the money to pay off debt and fund road projects.

7. Indiana Toll Road
"The Crossroads of America" is owned by the crossroads of Spain and Australia. Like the Chicago Skyway, the Indiana Toll Road is owned by Macquarie Infrastructure Group.

bull1.jpg8. Merrill Lynch
The iconic bull down in Battery Park may no longer represent United States' economic fortitude. In January, ML raised $6.6 billion from the sale of its preferred stock to three foreign investors: Korean Investment Corporation, Japan's Mizuho Financial Group Inc, and the Kuwaiti Investment Authority.

9. Trader Joe's
Trader Joe, a manager of Rexall drugs, bought the Rexall store chain, changed the name and began offering exotic, environmental, and healthy food. In 1979 ALDI, a German company, bought out the company.

10. Genentech
The largest biotech firm in America is actually owned by the Swiss. In fact, they just made an unsolicited offer to acquire the 44% of the firm that it does not already own for about $44 billion.

Be sure to check out more of what Diana learned today here.

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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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Stephen Missal
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]