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Foraging fits a pattern

The Hadza people of Tanzania are among the last hunter-gatherer groups on Earth, foraging on foot for most of their food. Now scientists have analyzed their movements and determined that they fit a mathematical pattern that also works for sharks, honeybees and other foraging animals.

The pattern, called the Lévy walk, involves a series of short movements in one area combined with a few longer treks to more distant areas.

“This helps avoid repeated visits to the same spot,” said an author of the study, David Raichlen, an anthropologist at the University of Arizona.

For the study, which appears in Proceedings of the National Academy of Sciences, Raichlen and his colleagues asked Hadza men and women to wear GPS wristwatches so their movements could be tracked from dawn to dusk as they hunted for meat, berries, tubers, honey and other food.

The research suggests that the Lévy walk could be fundamental to the way humans experience and move about the world, Raichlen said. Previous research has also identified the same pattern in the way people move around amusement parks and in urban environments.

“It’s not all that surprising when you think what we all do on a daily basis,” he said. “I go to work and back every day, maybe the grocery store, and then every once in a while I make a longer movement to a place farther away.”

Keeping faces straight

A new computer algorithm can subtly modify the image of a person’s face to make it easier or harder to remember.

The formula was developed by researchers at MIT who presented volunteers with thousands of images of faces and evaluated their ability to remember those faces. Each picture was given a score, based on how memorable it was.

When given a face to modify, the algorithm generates thousands of copies of it and then modifies each one subtly, refining it further as it goes along. The researchers do not know exactly what the changes are, said the study’s senior author, Aude Oliva, who presented the work at the International Conference on Computer Vision. The algorithm may add the slightest raise of an eyebrow or the slightest squint of an eye.

“It looks like the faces that are more memorable are a little slimmer, but that is just my interpretation,” Oliva said. “And those that are more forgettable look a little rounder, but we really do not know.”

– New York Times