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Kristina Killgrove

Teeth and Bones from Ancient Rome Hold Clues to Migration and Slavery

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Kristina Killgrove

There’s an old saying that “all roads lead to Rome.” With good reason, too. Rome during the Empire was massive, with crowded neighborhoods boasting a population density comparable to New York, and with roads snaking throughout the Empire to help provision its capital. Along with goods came people; both immigrants looking for jobs or education and slaves brought to Rome to serve the upper classes. My new study, out today in PLOS One, uses teeth from Roman skeletons to start a conversation about migration to the capital during the Imperial period (1st–3rd century CE). 

We know from Roman history and from studies of ancient demography that the rate of migration to Rome had to be relatively high, and we know that many citizens could move freely around the Empire. But archaeologically speaking, migrants are practically invisible. Unless they were wealthy enough to leave monuments to their foreignness, these individuals are hard to see—especially among the lower classes and slaves who made the journey to Rome.

But Roman skeletons hold different information than historical records and archaeological remains like material culture. Bones and teeth can be analyzed by bioarchaeologists to reveal what someone ate, what diseases they had, and where they were born. So skeletal analysis is starting to provide new answers to longstanding questions about ancient Roman lives, including people’s origins. 

Using molars from two cemeteries in Rome that date to the 1st–3rd centuries CE, my colleague Janet Montgomery and I analyzed the isotope ratios of strontium in 105 people and of oxygen in 55 people who were likely among the lower class, judging by their simple burials with few grave goods (objects buried with them). The ratio between two isotopes, or variants of an element, reflects the environment where a person lived while their teeth were forming in childhood. By comparing the strontium and oxygen isotope ratios present in the skeletons with the ratios expected for people raised in Rome, we could identify individuals whose isotope ratios did not correspond with an origin there.

Since Imperial Rome was a very complex place—water was brought in via aqueducts from the east and wheat was brought in from as far away as North Africa—it is easiest to see immigrants whose isotopes are very far outside the norm for Rome. Out of more than 100 skeletons, we found four people—three adult males and one adolescent—who we are confident were from elsewhere. The adolescent's isotope ratios are consistent with an origin in Africa, and the males' are consistent with homelands in the Alps and Apennines.

The isotope ratios of another four people, including two older children and a male and a female teenager, are less clear-cut, but these individuals were probably also not from Rome. Isotope analysis isn't a biological GPS, though, so while we can't be sure exactly where they came from, it seems that people arrived from all compass points.

Given what we know from history, it is not surprising to find migrants among these skeletons, but it is a little surprising that we found so few. The scale of slavery and migration to Rome during the Empire means we should expect more people to be migrants. However, isotope analysis cannot distinguish among people who were born in Rome and people who were born in another, isotopically similar location. We may be missing some migrants who are hidden within the data.

The people who came to Rome as children and died in Rome as children are particularly interesting. Of the eight probable immigrants, there are three adults, three teenagers, and two older children. This number of juveniles was unexpected because both voluntary migrants and slaves mentioned in the historical records are usually men. Based on their isotope ratios, two of the juveniles came from somewhere with older geology, like northern Italy, while the other three came from someplace warmer and drier than Rome, like North Africa.

One adolescent in particular, whose eye orbit with an anemic condition is seen in the photo below, has a tooth with very different strontium, oxygen, and carbon isotope ratios compared to what we'd expect from Rome. His bones showed, though, that his carbon isotope ratio just prior to his death was in line with Rome. This indicates he changed his diet after migrating. While it makes sense that we'd see migrants adopting the diet of their new home at Rome, this is the first study to make that connection explicit through isotopes.

Based on skeletons alone, we've discovered that people of both sexes migrated, often as children, and we've demonstrated a change in diet following migration.

Why did they come to Rome? Some were motivated to migrate in antiquity for many of the reasons people are motivated today: to find a better job, to be educated, to make a better life. But many were forced to come. We know from historical records that the scale of slavery in the Roman Empire dwarfed the amount of voluntary migration. Still, slavery in ancient Rome was often a temporary legal status, and manumission of slaves was common.

There is nothing in the isotopes, the skeletons, or the graves that clearly identifies slaves or voluntary immigrants. This work, though, opens up a new way of looking at migration to Rome that may eventually yield new information on the history of slavery and the experiences of Roman slaves.

The work that I and many colleagues are doing in the bioarchaeology of ancient Rome demonstrates that physical remains can give us new information about a culture that people have been studying for millennia already. The bodies of people throughout the Empire are helping us flesh out the skeleton of Roman history with the experiences of the people whose stories have not yet been told.

My PLOS One article is freely downloadable here:

Killgrove K, Montgomery J (2016) All Roads Lead to Rome: Exploring Human Migration to the Eternal City through Biochemistry of Skeletons from Two Imperial-Era Cemeteries (1st-3rd c AD). PloS ONE 11(2): e0147585. doi: 10.1371/journal.pone.0147585.

All images courtesy of Kristina Killgrove

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iStock // Ekaterina Minaeva
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Man Buys Two Metric Tons of LEGO Bricks; Sorts Them Via Machine Learning
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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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Why Your iPhone Doesn't Always Show You the 'Decline Call' Button
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iStock

When you get an incoming call to your iPhone, the options that light up your screen aren't always the same. Sometimes you have the option to decline a call, and sometimes you only see a slider that allows you to answer, without an option to send the caller straight to voicemail. Why the difference?

A while back, Business Insider tracked down the answer to this conundrum of modern communication, and the answer turns out to be fairly simple.

If you get a call while your phone is locked, you’ll see the "slide to answer" button. In order to decline the call, you have to double-tap the power button on the top of the phone.

If your phone is unlocked, however, the screen that appears during an incoming call is different. You’ll see the two buttons, "accept" or "decline."

Either way, you get the options to set a reminder to call that person back or to immediately send them a text message. ("Dad, stop calling me at work, it’s 9 a.m.!")

[h/t Business Insider]

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