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New York’s Trans Fat Ban Reduced Heart Attacks and Strokes

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Banning trans-fatty acids had a measurable impact on public health in the state of New York, according to a new study recently highlighted by Popular Science. A review of New York State Department of Public Health data from 2002 to 2013, published in the JAMA Cardiology, finds that there were 6.2 percent fewer hospital visits related to heart attacks and strokes in counties that banned foods that contained trans-fatty acids (trans fats) compared to counties that didn’t have a ban in place.

In 2007, New York City, which has five counties, became the first U.S. metro area to ban trans fats in restaurants, bakeries, and other eateries. Six other counties in New York state followed suit over the subsequent five years. Trans fats in foods like Twinkies, Girl Scout Cookies, coffee creamers, and microwave popcorn typically come from partially hydrogenated oils, which have been found to increase the risk of stroke, heart disease, and more. The bans did not apply to packaged food, so people in those 11 counties likely still had some trans fats in their diets, but nonetheless were eating less than their counterparts in the 25 counties in the study without a ban in place.

The study, led by Yale cardiologist Eric Brandt, found that within three years of instituting a ban on trans fats in restaurant foods, counties saw a 6.2 percent total decline in people who went to the hospital for heart attacks and strokes. The data showed that specifically, there was a 7.8 percent decline in heart attacks and 3.6 percent decline in strokes for both men and women.

The FDA began requiring companies to list the amount of trans fats contained in packaged food in 2006, causing many companies to begin reducing or eliminating them from products. After New York City instituted its trans fats ban, California followed suit, as did several individual cities like Philadelphia and Seattle.

It’s impossible to say that the decline in hospital visits was solely due to a reduction in trans fats in diets, but consider how harmful research has shown them to be: Eating just 2 grams of trans fats a day is considered to pose a dangerous risk to your cardiovascular health.

Despite the bans, trans fats still pose a risk to consumers. Any product with less than 0.5 grams per serving can claim to have 0 grams of trans fat, meaning that some foods (like Girl Scout Cookies) can market themselves as trans fat–free but still contain partially hydrogenated oils. That will change soon, though. In 2018, trans fats will no longer be “generally recognized as safe” by the FDA. This will essentially ban the unhealthy oils—since companies would have to prove they are safe to eat before using them.

[h/t Popular Science]

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iStock // Ekaterina Minaeva
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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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Name the Author Based on the Character
May 23, 2017
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