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    A sarcophagus discovered in 2009 in an Egyptian burial chamber came with a complicated history: Ancient writing on the stone container showed that it had been used twice, but while its second occupant, the 21st dynasty high priest Menkheperre, was known, the first owner had remained a mystery — until now.

    New clues have surfaced as a result of Frederic Payraudeau, an associate professor in Egyptology at Sorbonne University in Paris, reexamining a fragment of the granite sarcophagus and deciphering the hieroglyphs engraved on it. Tucked away in the cartouche, an oval-shaped ornament often found in tombs, he found a name of a very recognizable figure: Ramesses II.
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    The findings, published in the journal Revue d’Egyptologie, add to the lore of Ramesses II, also known as Ozymandias and one of Egypt’s most celebrated pharaohs. It also fills a gap in our understanding of how sarcophagi were used to entomb kings.
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    Another coffin belonging to Ramesses II was discovered in 1881 near Luxor, but the sarcophagus fragment analyzed in the study was found in Abydos, a city about 40 miles (64 kilometers) to the northwest in a straight line.

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    Wild African elephants may address each other using individualized calls that resemble the personal names used by humans, a new study suggests.

    While dolphins are known to call one another by mimicking the signature whistle of the dolphin they want to address, and parrots have been found to address each other in a similar way, African elephants in Kenya may go a step further in identifying one another.

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    The idea was that “if the calls contained something like a name, then you should be able to figure out who the call was addressed to just from the acoustic features of the call itself,” said lead study author Mickey Pardo, an animal behaviorist and postdoctoral fellow at Cornell University in New York.

    The researchers found that the acoustic structure of calls varied depending on who the target of the call was.

    The machine-learning model correctly identified the recipient of 27.5% of calls analyzed, “which may not sound like that much, but it was significantly more than what the model would have been able to do if we had just fed it random data,” Pardo told CNN.

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