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How to Find Your Chronotype—And How Knowing It Can Help You

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You probably know if you’re an early bird or a night owl. But did you know that there are two other in-between types? Discovering your unique bio-time—a.k.a. your chronotype—can help dictate the best time for you to make an important decision or take the next step in your career.

Michael Breus, a clinical psychologist and fellow of the Academy of Sleep Medicine, examined more than 200 studies to write his new book, out September 13, called The Power of When. Take the 45-second free online quiz to learn your unique chronotype (Breus divides everyone into four categories: Bears, Wolves, Dolphins, and Lions), and then read on to see when you should be doing what. 

THE BEST TIME TO MAKE A DECISION

In order to make a decision, your brain needs to function on an emotional level and on a logical level, Breus says. In emotional terms, if you feel afraid and insecure, it can cause you to act cautiously. Sleep deprivation and your tendency towards procrastination also affect your decision-making skills, but the biggest factor is your personal circadian rhythm, and this depends on your chronotype.

According to Breus, Lions will make the best decisions first thing in the morning, from 6:00 to 11:00 a.m. “You’ll be alert, ready to go, understanding what’s happening,” Breus says. Bears, who wake a little later, should plan major moves for before lunch (between 8:00 and 11:00 a.m.), while Dolphins do best from 10:00 a.m. to 2:00 p.m.

Wolves, who are night people, have two windows for optimal decisiveness: 12:00 to 2:00 p.m. and again from 5:00 p.m. to 1:00 a.m. They need the break in the middle of the day because their sugar levels drop, and they shouldn’t make a decision on an empty stomach. Also, right before bed in the evening is prime decision-making time for everyone, because creative ideas often come when you’re about to fall asleep and your mind is a little distracted, Breus says. 

THE BEST TIME TO SCHEDULE A JOB INTERVIEW

In order to game your job interview, it’s best to know the circadian rhythm of your interviewer as well. “Most leaders are Lions anyway,” Breus says, explaining that they’re at their best first thing in the morning. But are you? You don’t want to be there at 8:00 a.m. if you aren’t going to be able to function.

On the flip side, you also don’t want to be the last interview of the day. “If [your interviewer] thought that everyone was good, they’re going to downgrade you because they’re going to think that they need to think that someone wasn’t good . . . and you’re up, so that must be you,” Breus says. Finding the right balance "is not an exact science," Breus says, "but it works well.”

THE BEST TIME TO ASK FOR A RAISE

First, it’s important to determine the circadian rhythm of your boss. Take notice of the time they arrive in the office relative to your company's required start-time. Say work starts at 9:00 a.m.: If they stroll through the doors at 7:30, they’re probably a Lion. Arriving at 8:30 makes them a Bear, and 10:00 a.m. (in this scenario) probably means they're a Wolf. If you’re getting emails from them at all times of the night, they’re probably a Dolphin.

Don’t time the question too close to lunch, because no one wants to have a big conversation when their blood sugar is low and they’re heading out to grab a sandwich. Right after lunch is best, and your boss's preferred lunchtime most likely depends once again on their chronotype. For Lions, it's likely around 12:30 p.m.; Bears at 1:00 , Wolves between 2:00 and 3:00, and Dolphins at around 3:30.

Next, choose the day. “People become more and more positive as the week goes forward,” he says. Friday is the most positive day, and most people are happier later in the day. But you don’t want to schedule anything for after 4:00 p.m., because anything past 4:00 on a Friday is margarita time, Breus says.

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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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What Happened to Jamie and Aurelia From Love Actually?
May 26, 2017
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Fans of the romantic-comedy Love Actually recently got a bonus reunion in the form of Red Nose Day Actually, a short charity special that gave audiences a peek at where their favorite characters ended up almost 15 years later.

One of the most improbable pairings from the original film was between Jamie (Colin Firth) and Aurelia (Lúcia Moniz), who fell in love despite almost no shared vocabulary. Jamie is English, and Aurelia is Portuguese, and they know just enough of each other’s native tongues for Jamie to propose and Aurelia to accept.

A decade and a half on, they have both improved their knowledge of each other’s languages—if not perfectly, in Jamie’s case. But apparently, their love is much stronger than his grasp on Portuguese grammar, because they’ve got three bilingual kids and another on the way. (And still enjoy having important romantic moments in the car.)

In 2015, Love Actually script editor Emma Freud revealed via Twitter what happened between Karen and Harry (Emma Thompson and Alan Rickman, who passed away last year). Most of the other couples get happy endings in the short—even if Hugh Grant's character hasn't gotten any better at dancing.

[h/t TV Guide]

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