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YouTube // Nature Video

Did Lucy Die After Falling out of a Tree?

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YouTube // Nature Video

Not everything is like riding a bicycle; some skills in life are more of the use-it-or-lose-it variety. Researchers say Lucy may have died from a fall from a tree, possibly as a consequence of losing her ape ancestors’ tree-climbing skills. They published their controversial findings in the journal Nature.

The 3.2-million-year-old remains of an Australopithecus afarensis woman nicknamed Lucy have captivated the world since their discovery in Ethiopia in 1974. Her remains revealed to us the first human ancestors to have walked upright. In 2006, to fan the flames of Lucy’s fame, the Ethiopian government scheduled a tour for Lucy (also known as AL 288-1 and Dinknesh) with as many as 10 museum stops along the way. Many archaeologists feared that travel would cause irreparable damage to the one-of-a-kind skeleton. But the tour went on. During Lucy’s stop at the University of Texas, researchers pounced on the opportunity to put her bones in an x-ray computed tomography (CT) scanner.

Lucy’s distal radius undergoes computed tomographic scanning. Image credit: Marsha Miller, UT Austin

Using the scanner, the team produced 35,000 high-resolution “slices” of Lucy’s remains, which then allowed them to create a true-to-life 3D rendering that would stick around even after Lucy left.

Paleoanthropologist and project leader John Kappelman was examining the rendering when he saw something unusual: a strange break in Lucy’s right humerus (upper arm bone). In comparing the prehistoric injury to images of modern bone breakage, he realized it looked an awful lot like a four-part proximal humeral fracture, in which a blow to the shoulder blade smashes down the head of the humerus, compressing it into the shaft of the bone. Today, this kind of injury is common in car accidents when people have used their hands to brace against the dashboard, but it’s also typical in falls from great heights.

Kappelman and his colleagues then used a 3D printer to create a hard copy of the bones. They brought the newly made remains to nine orthopedic specialists, who all agreed with Kappelman’s initial assessment of a four-part proximal fracture. They suggest her injuries are consistent with someone who had fallen from a height of approximately 45 feet—about as high in the trees as chimpanzees typically build their sleeping nests—at a speed of about 37 mph.

“It may well have been the case that adaptations that permitted her to live more efficiently on the ground compromised her ability to move safely in the trees—and may have predisposed her kind to more falls,” Kappelman told Science.

Not everyone is convinced. Other archaeologists argue that other parts of Lucy’s body were far more fractured than they would have been after a fall. Of her shattered ribs, Kent State University biological anthropologist Owen Lovejoy said in Science, “you couldn’t do that with a shotgun blast.”

Then there’s the fact that Lucy’s bones could easily have been damaged after she died. Paleoanthropologist Don Johanson of Arizona State University, who discovered Lucy in 1974, is skeptical. “Terrestrial animals like antelopes and gazelles, elephants and rhinos and giraffes—all these bones show very similar fracture and breakage patterns as Lucy,” he pointed out to Science. “You can be sure they didn’t fall out of trees.”

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Google's AI Can Make Its Own AI Now
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iStock

Artificial intelligence is advanced enough to do some pretty complicated things: read lips, mimic sounds, analyze photographs of food, and even design beer. Unfortunately, even people who have plenty of coding knowledge might not know how to create the kind of algorithm that can perform these tasks. Google wants to bring the ability to harness artificial intelligence to more people, though, and according to WIRED, it's doing that by teaching machine-learning software to make more machine-learning software.

The project is called AutoML, and it's designed to come up with better machine-learning software than humans can. As algorithms become more important in scientific research, healthcare, and other fields outside the direct scope of robotics and math, the number of people who could benefit from using AI has outstripped the number of people who actually know how to set up a useful machine-learning program. Though computers can do a lot, according to Google, human experts are still needed to do things like preprocess the data, set parameters, and analyze the results. These are tasks that even developers may not have experience in.

The idea behind AutoML is that people who aren't hyper-specialists in the machine-learning field will be able to use AutoML to create their own machine-learning algorithms, without having to do as much legwork. It can also limit the amount of menial labor developers have to do, since the software can do the work of training the resulting neural networks, which often involves a lot of trial and error, as WIRED writes.

Aside from giving robots the ability to turn around and make new robots—somewhere, a novelist is plotting out a dystopian sci-fi story around that idea—it could make machine learning more accessible for people who don't work at Google, too. Companies and academic researchers are already trying to deploy AI to calculate calories based on food photos, find the best way to teach kids, and identify health risks in medical patients. Making it easier to create sophisticated machine-learning programs could lead to even more uses.

[h/t WIRED]

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Land Cover CCI, ESA
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Afternoon Map
European Space Agency Releases First High-Res Land Cover Map of Africa
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Land Cover CCI, ESA

This isn’t just any image of Africa. It represents the first of its kind: a high-resolution map of the different types of land cover that are found on the continent, released by The European Space Agency, as Travel + Leisure reports.

Land cover maps depict the different physical materials that cover the Earth, whether that material is vegetation, wetlands, concrete, or sand. They can be used to track the growth of cities, assess flooding, keep tabs on environmental issues like deforestation or desertification, and more.

The newly released land cover map of Africa shows the continent at an extremely detailed resolution. Each pixel represents just 65.6 feet (20 meters) on the ground. It’s designed to help researchers model the extent of climate change across Africa, study biodiversity and natural resources, and see how land use is changing, among other applications.

Developed as part of the Climate Change Initiative (CCI) Land Cover project, the space agency gathered a full year’s worth of data from its Sentinel-2A satellite to create the map. In total, the image is made from 90 terabytes of data—180,000 images—taken between December 2015 and December 2016.

The map is so large and detailed that the space agency created its own online viewer for it. You can dive further into the image here.

And keep watch: A better map might be close at hand. In March, the ESA launched the Sentinal-2B satellite, which it says will make a global map at a 32.8 feet-per-pixel (10 meters) resolution possible.

[h/t Travel + Leisure]

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