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Women of the Venetian Renaissance

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We're doing a week of women on "Feel Art Again." Today's post brings you the four most prominent female artists of the Venetian Renaissance: Sofonisba Anguissola, Diana Mantuana, Marietta Robusti, and Lavinia Fontana.

Sofonisba Anguissola (1532-1625) began training under Bernardino Campi when she was only 14; she later trained under Bernardino Gatti. Anguissola's apprenticeships were unusual, as most women of the time only trained under their family members. Her apprenticeships made it more acceptable for other women to be students of art. When she was 22, she was introduced to Michelangelo, and began an informal training with the master that lasted at least 2 years. He would give her advice on drawings she made based on sketches from his notebook that he gave her. Anguissola was a court painter and art tutor to the queen in the Spanish Court of Philip III. King Philip III was so supportive of Anguissola that he even arranged her marriage at age 38 to Don Francisco de Moncada and provided her dowry.
Shown at left is Anguissola's "The Chess Game" (1555)

ScultoriDiana Mantuana (1535-1612) trained as an engraver—an uncommon profession for women of the time—under her father, an engraver for the Mantuan court. She received a Papal Privilege to sell her engravings under her two variations of her name, making her the first woman to sell work under her own name (or at least in Rome). Mantuana was a skilled businesswoman who actively promoted herself and her husband, an architect, through her lengthy dedications. Since her death, Mantuana has been known by several names—Diana Mantuana and Diana Mantovana are the names she herself used, the surname Ghisi was ascribed to her because of a mistaken relationship to another engraver, and the surname Scultori was assumed for her by art historians.
Shown at left is Mantuana's "Latona Giving Birth to Apollo and Diana on the Island of Delos"

RobustiMarietta Robusti (c.1555-1590) was the daughter of the famous painter Jacopo Robusti, from whom she inherited the nickname la Tintoretta. Robusti had an especially close relationship with her father. She served an apprenticeship in his studio and even dressed like a boy so she could go everywhere with him. Court painter offers from both Emperor Maximilian and King Philip II were turned down by her father because he couldn't bear to part with his dear daughter. Although Robusti was a well-known portraitist with a "considerable reputation" in her day, painting everybody who was anybody in Venice, only one painting can be conclusively attributed to her today—her "Self Portrait" (1580) at left.

FontanaLavinia Fontana (1552-1614) was also the daughter of a prominent painter, Prospero Fontana. She married Paolo Zappi, who became her painting assistant and a househusband while Fontana supported the family on her artwork. They had 11 children—yes, eleven—but only 3 outlived their mother. In 1603, Fontana was invited to Rome (with her family in tow) by Pope Clement VIII. There, she gained the patronage of the Buoncampagni and even painted Pope Paul V. Fontana is attributed with the largest oeuvre for a pre-1700 female artist with 100 documented works; 32 signed and dated works are known today, with 25 more also attributed to her.
Shown at left is Fontana's "Newborn Baby in a Crib" (1583)

"Feel Art Again" appears three times a week. Looking for a particular artist? Visit our archive for a complete listing of all 250+ artists that have been featured. You can e-mail us at feelartagain@gmail.com with details of current exhibitions, for sources or further reading, or to suggest artists. Or you can head to our Facebook page, where you can do everything in one place.

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iStock // Ekaterina Minaeva
technology
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Man Buys Two Metric Tons of LEGO Bricks; Sorts Them Via Machine Learning
May 21, 2017
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iStock // Ekaterina Minaeva

Jacques Mattheij made a small, but awesome, mistake. He went on eBay one evening and bid on a bunch of bulk LEGO brick auctions, then went to sleep. Upon waking, he discovered that he was the high bidder on many, and was now the proud owner of two tons of LEGO bricks. (This is about 4400 pounds.) He wrote, "[L]esson 1: if you win almost all bids you are bidding too high."

Mattheij had noticed that bulk, unsorted bricks sell for something like €10/kilogram, whereas sets are roughly €40/kg and rare parts go for up to €100/kg. Much of the value of the bricks is in their sorting. If he could reduce the entropy of these bins of unsorted bricks, he could make a tidy profit. While many people do this work by hand, the problem is enormous—just the kind of challenge for a computer. Mattheij writes:

There are 38000+ shapes and there are 100+ possible shades of color (you can roughly tell how old someone is by asking them what lego colors they remember from their youth).

In the following months, Mattheij built a proof-of-concept sorting system using, of course, LEGO. He broke the problem down into a series of sub-problems (including "feeding LEGO reliably from a hopper is surprisingly hard," one of those facts of nature that will stymie even the best system design). After tinkering with the prototype at length, he expanded the system to a surprisingly complex system of conveyer belts (powered by a home treadmill), various pieces of cabinetry, and "copious quantities of crazy glue."

Here's a video showing the current system running at low speed:

The key part of the system was running the bricks past a camera paired with a computer running a neural net-based image classifier. That allows the computer (when sufficiently trained on brick images) to recognize bricks and thus categorize them by color, shape, or other parameters. Remember that as bricks pass by, they can be in any orientation, can be dirty, can even be stuck to other pieces. So having a flexible software system is key to recognizing—in a fraction of a second—what a given brick is, in order to sort it out. When a match is found, a jet of compressed air pops the piece off the conveyer belt and into a waiting bin.

After much experimentation, Mattheij rewrote the software (several times in fact) to accomplish a variety of basic tasks. At its core, the system takes images from a webcam and feeds them to a neural network to do the classification. Of course, the neural net needs to be "trained" by showing it lots of images, and telling it what those images represent. Mattheij's breakthrough was allowing the machine to effectively train itself, with guidance: Running pieces through allows the system to take its own photos, make a guess, and build on that guess. As long as Mattheij corrects the incorrect guesses, he ends up with a decent (and self-reinforcing) corpus of training data. As the machine continues running, it can rack up more training, allowing it to recognize a broad variety of pieces on the fly.

Here's another video, focusing on how the pieces move on conveyer belts (running at slow speed so puny humans can follow). You can also see the air jets in action:

In an email interview, Mattheij told Mental Floss that the system currently sorts LEGO bricks into more than 50 categories. It can also be run in a color-sorting mode to bin the parts across 12 color groups. (Thus at present you'd likely do a two-pass sort on the bricks: once for shape, then a separate pass for color.) He continues to refine the system, with a focus on making its recognition abilities faster. At some point down the line, he plans to make the software portion open source. You're on your own as far as building conveyer belts, bins, and so forth.

Check out Mattheij's writeup in two parts for more information. It starts with an overview of the story, followed up with a deep dive on the software. He's also tweeting about the project (among other things). And if you look around a bit, you'll find bulk LEGO brick auctions online—it's definitely a thing!

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iStock
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Scientists Think They Know How Whales Got So Big
May 24, 2017
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iStock

It can be difficult to understand how enormous the blue whale—the largest animal to ever exist—really is. The mammal can measure up to 105 feet long, have a tongue that can weigh as much as an elephant, and have a massive, golf cart–sized heart powering a 200-ton frame. But while the blue whale might currently be the Andre the Giant of the sea, it wasn’t always so imposing.

For the majority of the 30 million years that baleen whales (the blue whale is one) have occupied the Earth, the mammals usually topped off at roughly 30 feet in length. It wasn’t until about 3 million years ago that the clade of whales experienced an evolutionary growth spurt, tripling in size. And scientists haven’t had any concrete idea why, Wired reports.

A study published in the journal Proceedings of the Royal Society B might help change that. Researchers examined fossil records and studied phylogenetic models (evolutionary relationships) among baleen whales, and found some evidence that climate change may have been the catalyst for turning the large animals into behemoths.

As the ice ages wore on and oceans were receiving nutrient-rich runoff, the whales encountered an increasing number of krill—the small, shrimp-like creatures that provided a food source—resulting from upwelling waters. The more they ate, the more they grew, and their bodies adapted over time. Their mouths grew larger and their fat stores increased, helping them to fuel longer migrations to additional food-enriched areas. Today blue whales eat up to four tons of krill every day.

If climate change set the ancestors of the blue whale on the path to its enormous size today, the study invites the question of what it might do to them in the future. Changes in ocean currents or temperature could alter the amount of available nutrients to whales, cutting off their food supply. With demand for whale oil in the 1900s having already dented their numbers, scientists are hoping that further shifts in their oceanic ecosystem won’t relegate them to history.

[h/t Wired]

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