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Our Readers' Favorite Bookstore Cats (Volume One)

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One of the ways independent book stores distinguish themselves from the big chain stores is to make their shop into a literary home, where people like to hang out. Having a cat (or many cats) around is a simple way to do that -and it keeps the mice away! When 12 Bookstore Cats was posted last week, we received responses from dozens of bookstore cat fans, and tips on lots of cats to meet.

1. Sir Marjorie Lambshank III

The Park Slope Community Bookstore in Brooklyn has an entire menagerie of pets, although you'd never know it from looking through their website (however, the website is full of neat stuff, like their delivery offer). The store cat is named Sir Marjorie Lambshank III, and he (yes, he) has his own (one-post) blog. And Twitter feed. Sir Marjorie explains that the name "Marjorie" was given to mellow him out, and "Sir" was added to make it clear that Marjorie is a male.

2. Trini and 3. Ida B.

Wild Rumpus Books in Minneapolis has a variety of critters, including chickens, rodents, reptiles, and several Manx cats. The two pictured are Trini and Ida B. You'll see more of the children's book store's pets on their Facebook page.

4. Hodge

Selected Works Used Books & Sheet Music in Chicago employs Hodge to meet and greet book lovers. A customer talks about Hodge in this review:

...a gorgeous, soft-furred, grey mischief-maker who will claw at your leg when you sit down and sprawl in the middle of the floor right behind where you stand. But I'm already fond of the little devil, and s/he lends a lot of character to the place, so it's okay.

The store's Facebook page has an album of Hodge's photographs.

5. Fred

Columbia Books in Columbia, Missouri opened during the time I lived in the town, but that was long before Fred was born. Fred is a large, fluffy cat who likes to sprawl on the windowsills of the bookstore.

6. Won Ton

Won Ton is the mascot at Chop Suey Books in Richmond, Virginia. What little we know about Won Ton is from a collaborative poem written about him. He likes attention: of course, he's a cat! See lots more pictures at the store's Facebook page.

7. Franny

Skylight Books in Los Angeles has a web page devoted to their store mascot Franny. Franny is a young cat, having arrived at the bookstore as a three-month-old kitten in 2009. They also maintain a memorial page for the beloved previous cat, Lucy, who lived at the store nearly ten years until she died in 2007.

8. Felixia and 9. Bartleby Lucas

Adams Avenue Book Store is in San Diego. Information about the store's cats is relegated to the store's Facebook page, where I found pictures of Felixia and Bartleby Lucas. Bartleby Lucas (the lower cat shown) has his own Facebook page, where he lists his relationship status as "it's complicated".

10. Isbn and 11. Bob

Recycle Books in Campbell, California once had a cat named Isbn, who was given the "Best Bookstore Cat Name" by Publisher's Weekly. A customer informs us that Isbn (left) retired to live in a private home and the new store cat (right) is named Bob.

12. Hobo

From My Shelf Books in Wellsboro, Pennsylvania has a friendly cat named Hobo. Hobo has his hand, or paw, in everything: he writes a weekly book column for the local paper, he posed for the store's sign designed in his likeness, and he co-wrote a children's book with store owner Kevin Coolidge, called Hobo Finds a Home. It's an autobiography. Hobo also cuddles with customers every day.

13. and beyond: Chapel Hill Cats

Eric Johnson, who owns Recycle Books is also the proprietor of The Bookshop in Chapel Hill, North Carolina. The store has several cats on the premises, including this orange tabby in the window. Customers love the cats but leave no record of their names. Image by Flickr user bunchofpants.

If your favorite bookstore cat isn't listed here, it may be found in one of the previous posts, 12 Bookstore Cats and 8 Bookstore Cats. Or it may be in the next edition of the Bookstore Cat series!

See also: 8 Library Cats

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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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