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7 Great Places with Horrifying Names

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Itub/Wikimedia Commons

As you can’t judge a book by its cover, you can’t judge the people of some communities by the place name. After all, when you live in a place called Hell, you have to have a sense of humor. And many of them would love for you to visit!

1. Hell, Michigan

Photograph by Sswonk.

Hell, Michigan grew up around a grist mill on what is now named Hell Creek. The name “Hell” has a couple of legends associated with its origin. One attributes it to a resident overhearing a German conversation by travelers that said, "So schön hell!" which means "So beautifully bright!" Another quotes grist mill owner George Reeves as saying, about naming the town, "I don't care, you can name it Hell for all I care."

Hell is a tourist draw for its name, and takes advantage of it. Businesses are named for Halloween and afterlife themes, and there’s even a Damnation University that sells diplomas.

2. Shades Of Death Road

Photograph by Daniel Case.

Shades of Death is the name of a seven-mile road in Warren County, New Jersey. There are several theories as to why the road was named so. Nearby Ghost Lake was named for its ethereal fog, but there are also tales of murder and hauntings along the road and locations the road leads to. The highway department is constantly replacing signs that are stolen by souvenir-seekers.

3. Frankenstein, Missouri

Photograph from the Frankenstein, Missouri Facebook page.

Frankenstein is a tiny town of about 30 people just east of Jefferson City, Missouri. It was not named for Mary Shelley’s book nor the movie Frankenstein, but from an early citizen named Gottfried Franken, who donated land to erect a church in 1890. Frankenstein is a small but close-knit community that has its own Facebook page. It made national news in 1999 when Twentieth Century Fox staged an airdrop of 25 skydiving “Frankensteins” delivering VHS copies of the 25th anniversary edition of the movie Young Frankenstein.

4. Hell For Certain, Kentucky

Photograph by Nama.

Hell for Certain in Leslie County, Kentucky is officially named Dryhill for those who are offended at the community’s common name, which was drawn from nearby Hell for Certain Creek. The popular story of how the name came about tells of two men who rode their horses down the mountain.

One said, "This looks like hell." The other one said, "Yeah, for certain."

The U.S. Postal Service will not use the name (sometimes spelled Hell-Fer-Sartin), but named post offices Osha, Omarsville, and Kaliopi at different times.

5. Dead Women Crossing, Oklahoma

Image by Google Maps.

Dead Women Crossing is an unincorporated community in Custer County, Oklahoma. It was named after a murder/suicide/kidnapping that took place in 1905. Katie DeWitt James filed for divorce and her father saw Katie and her baby daughter off on a train to go stay with a cousin. Katie’s father did not hear from her for some time, and ultimately hired a detective to find her. Katie was last seen with Fannie Norton, a prostitute she met on the train. Norton denied any wrongdoing, but witnesses saw her go out with Katie and the baby and come back alone. The baby was recovered alive from a family who said Norton had given her to their young son. Norton, sensing the trouble she was in, drank poison and died. Katie’s body was later found near the river, shot through the skull and decapitated. The murder was attributed to Norton, and Katie’s estranged husband Martin Luther James inherited her property and took custody of the daughter. Some think he may have hired Norton to kill his wife. The legend that remains is that you can hear a woman crying for her baby at a bridge near the spot where Katie’s body was found.

6. Satan’s Kingdom

Photograph by Itub.

Satan's Kingdom State Recreation Area is near the town of New Hartford, Connecticut. Just east of town is an area called Satan’s Kingdom, so called because of the rough and marginalized characters who lived there. The signs designating the recreational area are often stolen because of the name.

7. Transylvania, Louisiana

Photograph by Infrogmation.

Transylvania, Louisiana got its name from Dr. W. L. Richards, an early landowner in the area. He named the town after Transylvania University, the college he attended in Lexington, Kentucky. But an honest history of the name didn’t stop legends of hauntings from growing up around the community. The town has a sense of humor about its name: They’ve painted a bat on their water tower. And being near the Louisiana swamplands, bats are heroes, as they eat mosquitos. Many gift shops sell Dracula figurines and merchandise as souvenirs.

See also: 8 Towns that are Numbered, The Origins of Weird State Park Names, 10 Town Names That Will Make You Hungry, Origins of 8 of the Strangest Place Names in Canada, and 10 Loud Places That Are Actually Nice and Quiet.

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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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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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