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Study Confirms What We Already Knew: Living Near Water Can Reduce Stress

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Beachfront property is considered the pinnacle of real estate for the views, the lifestyle, and, of course, the shoreline access. Everyone knows that being on the water makes us feel good, but now there's scientific proof: a new study confirms that living near a body of water improves wellbeing, even for city dwellers. The report was published in the journal Health & Place.

Scientific interest in so-called "blue" and "green" spaces is relatively recent, but cultural awareness of nature’s therapeutic power is quite old. Poets, Christian mystics, and nature-worshiping pagans alike all celebrated the power of the trees and tides. These days, we’re just getting good at quantifying it. 

Just a few weeks ago, for example, researchers published a study showing that living near lots of trees or other vegetation can actually extend a woman’s lifespan. The authors of that study cited three potential reasons green spaces might improve health: they provide inviting places to exercise, create opportunities to socialize, and they reduce stress.

The authors of the new paper believed that the same was true of blue spaces. They were especially interested in stress reduction, and whether blue and green spaces’ purported ability to calm would hold up in crowded city environments—specifically the capital city of Wellington, New Zealand. With nearly 500,000 citizens, the Wellington area is home to 10.6 percent of New Zealand’s entire population. 

The researchers pulled topographic information from national databases, mapping any forested areas, parks, and coastlines that would be visible to residents. They then looked to the 2011/12 New Zealand Health Survey (NZHS), which included questions on health, lifestyle, doctor visits, socioeconomic status, chronic medical issues, and mental wellbeing. Of the adults who took the survey, 442 were Wellington residents. 

The health and topographic data were then combined and analyzed. Some of the results were predictable, but others came as something of a surprise. "Increased views of blue space is significantly associated with lower levels of psychological distress," Michigan State University health geographer Amber L. Pearson said in a press statement. "However, we did not find that with green space."

Was it a money thing? After all, people in higher socioeconomic tiers tend to have better access to green and blue spaces, as well as medical care. But even after controlling for variables like sex, wealth, age, and local crime rates, their findings held true: being able to see the water was associated with better mental health for just about everyone. 

To ensure that their tests were accurate, the researchers decided to measure blue space visibility with a totally unrelated factor: toothlessness. If they found a significant  relationship between seeing water and missing teeth, they’d know something was wrong. But the relationship wasn’t there. 

Why would water help, but not trees? Pearson admits those particular results may have something to do with their study design. "It could be because the blue space was all natural, while the green space included human-made areas, such as sports fields and playgrounds, as well as natural areas such as native forests," Pearson said. "Perhaps if we only looked at native forests we might find something different."

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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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