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Marco Thines/Senckenberg Gesellschaft für Naturforschung

Irish Potato Famine Culprit Identified

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Marco Thines/Senckenberg Gesellschaft für Naturforschung

For the first time, scientists have used dried herbarium samples to decode the genome of a plant pathogen and its plant host. The pathogen in question is Phytophthora infestans, and its host, the simple potato—a duo responsible for the devastating famine that swept through Ireland in the mid-1800s, causing a mass exodus out of the Irish countryside as well as a ghastly death toll (due to both starvation and the rapid acceleration of disease) from which the country’s population is still recovering today. Through their research, a team of European molecular biologists have been allowed to confidently pin the agricultural disaster on a special strain of potato blight called HERB-1.

In order to examine the pathogen, molecular biologists had to reconstruct the spread of the potato blight pathogen using dried plants, a difficult feat that was helped immensely by samples so well preserved that, despite being 120 to 170 years old, they still contained several intact pieces of DNA. A fungus-like oomycete (microscopic, absorptive microorganisms that are often referred to as water molds), Phytophthora infestans has evolved over time. A different strand of the pathogen called US-1 was long thought to be the cause of the famine, but in their comparison of the historic samples with samples from today, the scientists have been able to conclude that US-1 is actually an evolved version of a separate, previous strain: HERB-1.

Thanks to the surprisingly well-preserved pathogen samples, the researchers have been able to estimate that the HERB-1 strain probably appeared in the early 1800s and continued to spread throughout the 19th century. Only in the 20th century, with the dawn of new potato varieties, did US-1 appear to take the place of HERB-1. While unique from US-1, the newly discovered HERB-1 shows definite signs of relation to its descendant strain. “Both strains seem to have separated from each other only years before the first major outbreak in Europe,” says Hernàn Burbano of the Max Planck Institute for Developmental Biology.

This conclusion is a huge breakthrough in a new area of research that seeks to understand the way pathogens evolve, as well as the effects of human activity on the growth of plant disease. "Perhaps this strain [HERB-1] became extinct when the first resistant potato varieties were bred at the beginning of the twentieth century," speculates Kentaro Yoshida from The Sainsbury Laboratory in Norwich. "What is for certain is that these findings will greatly help us to understand the dynamics of emerging pathogens. This type of work paves the way for the discovery of many more treasures of knowledge hidden in herbaria."

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iStock // Ekaterina Minaeva
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Man Buys Two Metric Tons of LEGO Bricks; Sorts Them Via Machine Learning
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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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iStock
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Why Your iPhone Doesn't Always Show You the 'Decline Call' Button
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iStock

When you get an incoming call to your iPhone, the options that light up your screen aren't always the same. Sometimes you have the option to decline a call, and sometimes you only see a slider that allows you to answer, without an option to send the caller straight to voicemail. Why the difference?

A while back, Business Insider tracked down the answer to this conundrum of modern communication, and the answer turns out to be fairly simple.

If you get a call while your phone is locked, you’ll see the "slide to answer" button. In order to decline the call, you have to double-tap the power button on the top of the phone.

If your phone is unlocked, however, the screen that appears during an incoming call is different. You’ll see the two buttons, "accept" or "decline."

Either way, you get the options to set a reminder to call that person back or to immediately send them a text message. ("Dad, stop calling me at work, it’s 9 a.m.!")

[h/t Business Insider]

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