The Development of the Journal Environment of Leonardo

We present animations based on the aggregated journal-journal citations of Leonardo during the period 1974-2008. Leonardo is mainly cited by journals outside the arts domain for cultural reasons, for example, in neuropsychology and physics. Articles in Leonardo itself cite a large number of journals, but with a focus on the arts. Animations at this level of aggregation enable us to show the history of the journal from a network perspective

Ariel - Volume 11 Number 2

Executive Editors Ellen Feldman Leonardo S. Nasca, Jr. Business .Managers Barbara L. Davies Martin B. Getzow News Editor Aaron D. Bleznak Features Editor Hugh A. Gelabert CAHS Editor Joan M. Greco Editorial Page Editor Samuel Markind Photography Editor Leonardo S. Nasca, Jr. Sports Editor Paul F. Mansfiel

Ariel - Volume 11 Number 1

Executive Editors Ellen Feldman Leonardo S. Nasca, Jr. Business Managers Barbara L. Davies Martin B. Getzow News Editor Aaron D. Bleznak Features Editor Dave Van Wagoner CAHS Editor Joan M. Greco Editorial Page Editor Samuel Markind Photography Editor Leonardo S. Nasca, Jr. Sports Editor Paul F. Mansfiel

Leonardo depicted America : misread as the moon

Leonardo da Vinci must have been aware that Columbus discovered new territories in the West. Until now, no material evidence had been found to substantiate this assumption. Here we show that Leonardo not only read Amerigo Vespucci’s letter (derived from a painted star constellation), but that he even drew a map including the New World, a drawing which was previously interpreted as a depiction of the Moon. Finally, Leonardo engraved his notion of this new continent on an ostrich egg globe (now known as the Da Vinci Globe) and made a copper cast of this. Both the cosmographic and cartographic clues demonstrate that Leonardo da Vinci knew about the fourth continent, to be named “America” in 1507, less than a decade after Columbus embarked upon its shores. This expansion of Leonardo’s cartographic legacy comes at a time of increased interest for such multi-disciplinary insights, as the world commemorates in 2019 the 500th anniversary of his death

Environment 2.0: Through Cracks in the Pavement - Leonardo Call For Papers

Call for papers for the Leonardo journal. A new relationship is emerging as computing migrates into the environment. Leonardo is soliciting texts that document the works of artists, researchers, and scholars involved in the exploration of sustainability in urban environments. Themes and issues may include: Sustainability in urban environments; Ubiquitous, pervasive, locative and mobile communication technology; Growing community; Sowing seeds of social change

A self-portrait of young Leonardo

One of the most famous drawings by Leonardo da Vinci is a self-portrait in red chalk, where he looks quite old. In fact, there is a sketch in one of his notebooks, partially covered by written notes, that can be a self-portrait of the artist when he was young. The use of image processing, to remove the handwritten text and improve the image, allows a comparison of the two portraits.Comment: Image processing, digital restoration, Leonardo da Vinc

Leonardo and the Whale

Around 1480, when he was 28 years old, Leonardo da Vinci recorded what may have been a seminal event in his life. In writing of his travels to view nature he recounted an experience in a cave in the Tuscan countryside: Having wandered for some distance among overhanging rocks, I can to the entrance of a great cavern... [and after some hesitation I entered] drawn by a desire to see whether there might be any marvelous thing within... [excerpt

"i have a feeling trump will win..................": Forecasting Winners and Losers from User Predictions on Twitter

Social media users often make explicit predictions about upcoming events. Such statements vary in the degree of certainty the author expresses toward the outcome:"Leonardo DiCaprio will win Best Actor" vs. "Leonardo DiCaprio may win" or "No way Leonardo wins!". Can popular beliefs on social media predict who will win? To answer this question, we build a corpus of tweets annotated for veridicality on which we train a log-linear classifier that detects positive veridicality with high precision. We then forecast uncertain outcomes using the wisdom of crowds, by aggregating users' explicit predictions. Our method for forecasting winners is fully automated, relying only on a set of contenders as input. It requires no training data of past outcomes and outperforms sentiment and tweet volume baselines on a broad range of contest prediction tasks. We further demonstrate how our approach can be used to measure the reliability of individual accounts' predictions and retrospectively identify surprise outcomes.Comment: Accepted at EMNLP 2017 (long paper