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Own a Piece of History (But Not a Very Important One)

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If you want to see some truly historic sports memorabilia, you've got to make the trip to a hall of fame or museum. After all, Babe Ruth's uniform isn't just hanging in any old closet. However, if you wanted to start your own museum, you could do that, too. Granted, you probably wouldn't have the same quality of exhibits, but eBay sellers do a thriving trade with people who want to own a piece of sports history, just not a particularly important piece. While nothing currently up for auction is as unsettling as a wad of Terry Francona's used gum and chewing tobacco, all manner of absurd game-used gems are available. Let's take a look at some of the more bizarre offerings a PayPal account can secure you right now:

Masumi Kuwata 2007 Pittsburgh Pirates Jersey

From 1986 to 2006, Kuwata was a legendary pitcher for the Yomiuri Giants of Japan's Central League. In 2007 he joined the Pirates as a 38-year-old rookie reliever and proceeded to get absolutely shelled, as often happens to the Pirates' pitchers. Over the course of 21 innings, he racked up an ERA of 9.43 and surrendered six home runs. For those of you who aren't baseball fans, I'll clarify: he was truly horrendous. And now you can own one of the jerseys he might have had on while pitching this batting practice! The starting bid is a scant $1,750, which means if you want to dress as a "Terrible Relief Pitcher" for Halloween this year, this costume pretty much pays for itself.

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Tony Dumas 1996-1997 Phoenix Suns Jersey

Dumas was a great target for mockery on some truly abysmal Dallas Mavericks teams, especially if you willfully mispronounced his last name. His career highlights include a 39-point game in 1996 and wrecking his knee while attempting his "Texas Twister" dunk in the 1995 NBA Slam Dunk contest. If you're a size 46 plus two inches of length, then you can slip into Tony's threads from his six-game stint with the Suns in the 1996-97 campaign. You probably wont' be able to pull off the Texas Twister, either.

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Kazuhisa Ishii Game-Used Bat

Kaz Ishii spent four decent years as a starting pitcher for the Los Angeles Dodgers and New York Mets before returning to his native Japan. Like most pitchers, Ishii wasn't much with the bat. In 164 big-league at-bats in his four-year career here, he got 18 hits for a cool .110 batting average with a single home run, exactly one more than you've probably hit in the majors. For only a $99 starting bid, you might be able to own the lumber that Ishii used to strike fear in the hearts of opposing pitchers. The other guys in your softball league will be terribly intimidated.

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NFL Game-Used ? Chin Strap

That rogue question mark isn't a typo "“ this one may not have been game-used at all. But really, can you afford to miss out on what could potentially be a piece of history? For only an opening bid of $10, you can get your hands on this handsome Riddell chin strap, complete with number 85 sticker on either side. The seller doesn't know what team or what player this gem might have come from or even if it was used in an NFL game, but if you want to own some memorabilia (or just keep a hat or helmet affixed to your head), this could be your bargain. Which number 85 might have worn it? Chad Johnson? Antonio Gates? An anonymous high-school tight end?

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Kansas City Scouts Game-Used Hockey Bag

This item appears to be a vinyl duffel bag used to transport hockey equipment during the New Jersey Devils' forerunners' stint in Kansas City from 1974-76. Granted, I wasn't alive and watching hockey in the mid-"˜70s, so this might be a stupid point. However, unless the rules of the game were much, much different then, it seems hard to believe that a duffel was "game used." "Season-used," maybe, but were players toting bags around on the ice before faceoffs? It's only going for $300, though, so you might as well buy it to find out.

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David LaFleur Dallas Cowboys Jersey

After an All-American career at LSU, tight end LaFleur became the Cowboys' first-round draft pick in 1997. Although LaFleur caught seven touchdowns in 1999, he was something of a bust in the NFL and was out of the league after the 2000 season. That doesn't mean you can't still buy his game-used jersey for a mere $200, thought. One look at the jersey itself illuminates part of why LaFleur was a favorite of NFL scouts: he's really, really tall. The jersey has seven extra inches of length, so even if you can't wear it to play football, it would make a sharp summer dress.

[Bid Now!]

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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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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]