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6 Winners and Losers of Globe Making

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Wikimedia Commons

Sometimes it’s good to be a little fish in a big pond—especially if you’re a municipality yearning for recognition on a mapmaker's globe.

It’s easy to miss the cut if your metropolis juts up against another, larger megalopolis, or a capital city. Or perhaps your hometown falls right in the path of a big, bold continent label. In either case, you might never locate your home, no matter how many libraries you visit.

At the other end of the scale are the obscure cities in the sparsely populated expanses of eastern Siberia, northern Africa, northern Canada and most of Australia. Just as nature abhors a vacuum, globe makers abhor empty space on their spherical canvas. With the choice between placing another dot on the map or leaving the space empty, globe makers tend to err on the side of more detail.

Here are a series of tiny towns you'll see on nearly every globe you can find—and some major cities that are almost always left off.

Small Towns on Nearly Every Globe

1. Oodnadatta, SA, Australia


Fewer than 300 residents. Abandoned by the railroad. Accessible only via hundreds of miles of unpaved roads. And on just about any globe you can find.

Why it makes an appearance is no mystery: There’s nothing else there. A sign on the Pink Roadhouse, a gathering place for locals and tourists alike, proclaims the town to be “the driest town, the driest state, of the driest continent.” Although the town was formerly a stop on the narrow gauge Central Australian Railway, stretching from Darwin in the north to Adelaide in the south, the town was bypassed by the new standard gauge railway in 1981.

2. Montpelier, VT, United States


If there’s one hard-and-fast rule of globe making, it’s this: When it comes to capital cities, size doesn’t matter. Montpelier, with fewer than 8000 residents, is the smallest capital in the United States. It’s less than 60 percent of the size of the next smallest capital (Pierre, SD).

In addition to being committed to rote memory by every elementary school student in America, Montpelier is also well known for something it doesn’t have—it’s the only state capital in the United States without a McDonald’s.

3. Any City in Greenland


Seriously, any of them. The capital, Nuuk, is home to fewer than 17,000 residents. After that, the next-largest city is under 6000. In all, there are just 13 towns in Greenland with more than 1000 residents, and all of them are on the coastline.

Depending on the age of your globe, you might find an entirely different set of municipal names. Following the establishment of the Greenland Home Rule government in 1979, names of Danish origin were changed to names derived from the three Inuit languages spoken in Greenland.

Huge Cities That Miss the Cut

4. Shenzhen, China


The world’s 11th most populous city is rarely seen on large-scale maps, let alone globes. But its lack of notoriety is through no fault of its own. With over 10.5 million residents in the city proper, Shenzhen would be in the upper third of national populations, falling in line between Greece and Rwanda. Shenzhen’s misfortune is to be located across the river from Hong Kong—a city with 3.4 million fewer residents.

Shenzhen and Hong Kong built each other in the latter half of the 20th century—Shenzhen as the manufacturing hub providing goods to the West, and British Hong Kong as the capitalist trade and financial center tapping directly into communist China’s factories and labor. In the world’s eye, though, Hong Kong wins out. The Globalization and World Cities Research Network labels Hong Kong as an Alpha+ City, where its larger neighbor to the north is deemed merely Beta-.

5. Louisville, Kentucky, United States


The largest city in Kentucky is the focus of the horseracing world each May, but good luck finding its location on a standard globe. Despite 610,000 residents within city limits, Louisville is usually the largest American city regularly missing the cut on globes.

There's a perfect storm working against the Derby City. Globe makers place higher importance on capitals (even state and provincial capitals) than population. Frankfort, with barely more than 25,000 residents, elbows its way to the front of the line. Meanwhile, the Ohio River, connecting the Rust Belt with the Mississippi, needs to be labeled somewhere in its relatively short run. Doing that in southern Ohio would make sense, if labels for Cincinnati and the state’s capital, Columbus, weren’t taking up space. More often than not, the northern border of Kentucky is the landing place for the river’s label, and Louisville finishes out of the money.

6. Dortmund, Germany


Dortmund may not be the first name that comes to mind when thinking of German cities—it may not even be in your top ten. But it’s the largest city in the Ruhrgebiet, Germany’s largest urban agglomeration and home to more than one out of ten Germans.

Most globes are designed with an eye toward relaying discrete units of information: nations, provinces, cities, rivers, and oceans. When cities grow together to form conurbations like the Ruhrgebiet, the whole may be greater than the sum of each part—even though none of the component cities are significant enough to appear on a standard classroom globe.

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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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iStock
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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