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Watercooler Ammo: And about that 19th Amendment...

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I really shouldn't be blogging about this -- after all, there's cleaning to be done, babies to be borne, kitchens to be barefoot in -- but Forbes has just published an article with a premise that falls somewhere on the misogyny continuum between Larry Summers and Satan: Don't marry career women. And that's just the headline. It also repeatedly refers to working women as "career girls" and includes this little gem:

If a host of studies are to be believed, marrying these women is asking for trouble. If they quit their jobs and stay home with the kids, they will be unhappy (Journal of Marriage and Family, 2003). They will be unhappy if they make more money than you do (Social Forces, 2006). You will be unhappy if they make more money than you do (Journal of Marriage and Family, 2001). You will be more likely to fall ill (American Journal of Sociology). Even your house will be dirtier (Institute for Social Research).

Even your house will be dirtier? Surely Bono wouldn't have signed off on this. The article is well on its way to being the talk of the blogosphere, and quite a few delicate flowers who have sought out careers and thus endangered their marriages will no doubt be getting ribbed about it at the watercooler all week. I don't want to cite a bunch of studies that undermine the Forbes article (although I certainly could), because studies of this kind, on both sides, are so often riddled with flaws. I also don't want to get into a discussion of individual choices, because that's exactly what they are. Instead, I'm just going to pose some questions for Michael Noer, the career boy who wrote the piece.

UPDATE! Forbes apparently took the piece down this afternoon!

UPDATE UPDATE! Forbes did not, however, manage to entirely eradicate the piece, which you can still read here.

Here's what Noer says: While everyone knows that marriage can be stressful, recent studies have found professional women are more likely to get divorced, more likely to cheat, less likely to have children, and, if they do have kids, they are more likely to be unhappy about it. Question: Is this also true of "professional men" vs. stay-at-home dads? Were Mr. Moms even included in any of the study samples? Are the women who have kids and are unhappy about "it" also unhappy because their husbands don't do an equal share of the housework?

And, of course, many working women are indeed happily and fruitfully married--it's just that they are less likely to be so than non-working women. Question: How does this jibe with the beginning of the piece, which says: "Just, whatever you do, don't marry a woman with a career"?

You will be more likely to fall ill (American Journal of Sociology). Even your house will be dirtier (Institute for Social Research). Question: Is that because you'll have to wipe your own nose and pick up your own socks? Do professional women with stay-at-home husbands have fewer colds and cleaner houses? In general, do women who work the same or more hours as their husbands do more or less housework than their husbands?

A few other studies, which have focused on employment (as opposed to working hours) have concluded that working outside the home actually increases marital stability, at least when the marriage is a happy one. But even in these studies, wives' employment does correlate positively to divorce rates, when the marriage is of "low marital quality." Question: So happy marriages get happier when women work, and unhappy marriages get unhappier? Could it be that the reason those marriages are bad is the same reason the men are displeased about their wives working?

The other reason a career can hurt a marriage will be obvious to anyone who has seen their mate run off with a co-worker: When your spouse works outside the home, chances increase they'll meet someone they like more than you. Question: Isn't this also true for men? Also, don't women meet people through volunteer work, PTA meetings, etc? Mr. Noer, are you suggesting that women should not interact with men other than their husbands, lest they get the vapors and swoon into bed with them?

According to a wide-ranging review of the published literature, highly educated people are more likely to have had extra-marital sex (those with graduate degrees are 1.75 more likely to have cheated than those with high school diplomas.) Additionally, individuals who earn more than $30,000 a year are more likely to cheat. Question: Again -- all true for men too, yes? If men should avoid women who make more than $30,000 a year, shouldn't women also do the same for men with that salary? Doesn't this mean that women should refuse to sleep with 99 percent of Forbes' demographic?

And if the cheating leads to divorce, you're really in trouble. ... Other studies have associated divorce with increased rates of cancer, stroke, and sexually-transmitted disease. Question: So if your wife works, you will get cancer?

I'm looking forward to Mr. Noer's responses.

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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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