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Letters from Our Readers

The New Yorker

Readers respond to Anthony Lane's essay about Christopher Marlowe, Lauren Collins's report on Uniqlo, and Dhruv Khullar's article about A.I. and medical diagnosis. I very much enjoyed Anthony Lane's gleeful review of Stephen Greenblatt's new biography of Christopher Marlowe (Books, September 15th). Lane reminds us that Marlowe took the plot of his play "Dido, Queen of Carthage" from Virgil's Aeneid. I'm not convinced, though, that Virgil would "blench" at Marlowe's opening scene, where a lecherous Jupiter entertains Ganymede, a boy, on his knee. Have another look at the opening verses of the Aeneid (especially Book I, line 28).


European spacecraft on way to Jupiter and its icy moons

Associated Press

A European spacecraft has blasted off on a quest to explore Jupiter and three of its ice-encrusted moons. Dubbed Juice, the robotic explorer set off on an eight-year journey Friday from French Guiana in South America, launching atop an Ariane rocket. Juice is taking a long, roundabout route. It should reach Jupiter in 2031 and spend three years buzzing Callisto, Europa and Ganymede. Then it will attempt to enter orbit around Ganymede, our solar system's largest moon. The three moons are believed to harbor underground oceans, where sea life could exist. If underground seas are confirmed, ice picks and a submarine could be next up.


NASA's Juno spacecraft snaps a stunning photo of Crescent Jupiter

Daily Mail - Science & tech

When it comes to out-of-this-world photographs, it's difficult to better a view that is impossible to see from Earth. But thanks to NASA's Juno spacecraft, this striking vista of Jupiter can be enjoyed as if you were riding along with the probe on one of its regular close flybys. Unlike the moon or Venus, this view of Jupiter in a crescent phase is impossible to see from Earth, even using a telescope. This is because Jupiter's orbit is outside Earth's, which means an observer on our planet can only see the side of Jupiter that is illuminated by the sun, so the planet always appears full. Citizen scientist Kevin M. Gill created the mosaic using raw data from the JunoCam instrument.


Ancient Roman mosaic reveals the dirty jokes that kept men amused as they urinated

Daily Mail - Science & tech

It seems humans have been scribbling dirty jokes on bathroom surfaces since the beginning of time. Archaeologists have discovered a pair of mosaics in a Roman-era latrine that depict well-known mythological scenes, each with its own raunchy spin. The 1,800-year-old mosaics, including an image of Narcissus admiring the reflection of his own penis, are an incredibly rare example of mosaic paving in the ancient latrines. Time has taken its toll on the ancient art piece, and only half of the Narcissus scene remains today. The mosaics feature humorous versions of the stories of Narcissus and Ganymede.


Cross-Language Latent Relational Search: Mapping Knowledge across Languages

AAAI Conferences

Latent relational search (LRS) is a novel approach for mapping knowledge across two domains. Given a source domain knowledge concerning the Moon, "The Moon is a satellite of the Earth," one can form a question {(Moon, Earth), (Ganymede, ?)} to query an LRS engine for new knowledge in the target domain concerning the Ganymede. An LRS engine relies on some supporting sentences such as ``Ganymede is a natural satellite of Jupiter.'' to retrieve and rank "Jupiter" as the first answer. This paper proposes cross-language latent relational search (CLRS) to extend the knowledge mapping capability of LRS from cross-domain knowledge mapping to cross-domain and cross-language knowledge mapping. In CLRS, the supporting sentences for the source pair might be in a different language with that of the target pair. We represent the relation between two entities in an entity pair by lexical patterns of the context surrounding the two entities. We then propose a novel hybrid lexical pattern clustering algorithm to capture the semantic similarity between paraphrased lexical patterns across languages. Experiments on Japanese-English datasets show that the proposed method achieves an MRR of 0.579 for CLRS task, which is comparable to the MRR of an existing monolingual LRS engine.