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Wikimedia Commons

9 Ways to Find Age Without a Calendar

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Wikimedia Commons

You can’t ask a tree or a whale how old they are, and most of them weren’t tracked from birth. So how do you tell their age? How do you find out the age of things without a calendar?

1. Dendrochronology

Literally translated, “dendrochronology” is “the study of tree time.” It’s more commonly known as tree-ring dating. Each year, trees in temperate climates form new rings in the summer and winter. During the summer, good growth conditions mean more growth, and less density to the new cells. Growth doesn’t stop during the winter, but instead happens at a much slower rate, forming a dense, dark ring. Rings can be counted while a tree is still alive by taking a core sample—a plug from the tree that goes all the way to its innermost rings. The size of tree rings can show what the environment in a region was like during a certain year, in addition to telling the age of the tree.

2. Otoliths

Removing an otolith from a red snapper, courtesy of Wikimedia Commons, fair use 

All vertebrates have otoliths (“ear stones”). They help us balance and interpret gravity and directional movement, and are pretty much the same size our entire lives. In fish, however, otoliths grow with their bodies, and much like tree rings, fish whose diet changes from season to season will show their age in their otolith rings. As most fish do not truly stop growing as long as they live, their otoliths continue to grow with them, even if it’s just a tiny bit every year.

3. Epiphyseal fusing

Tibia and fibula of 12-year-old, courtesy of Gilo1969, under Creative Commons license 

The epiphysis is a plate of quickly-growing cells at both ends of all long bones in the body. From birth to early adulthood, these plates change size and shape, until they disappear when growth ceases. Before they disappear, their size and degree of closure can give a rough estimate of the age at death of a human or a great ape. However, since those whose epiphyseal plates are visible to the extent of being useful past adolescence are not the norm, they’re most often used to find the age of children and young teens in criminal or anthropological forensic situations.

4. Tooth formation

Image courtesy of Dozentist, under Creative Commons license 

Babies are usually born without teeth, but that doesn’t mean they’re toothless—their teeth are still inside their skulls! Around the ninth week of gestation, there are detectable tooth “buds,” when the primary (also known as baby or milk) teeth begin to form. Even before the primary teeth come in, the permanent teeth begin to form right above them. Between birth and when the full set of permanent teeth come in (generally around 14 or 15), forensic analysis can compare the stage of development of the teeth, and estimate the age based on how far along the process was at time of death. It’s notable that even though wisdom teeth often don’t erupt until the late teens or early 20s, their development is so variable within modern humans (if the person even has them) that they’re infrequently used in aging skeletons less than several thousand years old.

5. Cementum annuli

What if a person’s teeth are already erupted and cemented in place? It turns out that the cementum, which anchors the tooth roots into place, produces microscopic rings of alternating collagen and mineralization patterns, allowing age at death to be determined so long as the remains have intact teeth, and have not been burned. “Cementum annuli” means “yearly cementum,” and we first realized that age could be determined by this method in deer. However, with deer (like many animals), it seems logical that in an environment with alternating food availabilities, the cementum would change patterns. It’s unknown why exactly the cementum does the same thing in humans, but it’s been so highly correlated to known ages that it’s an accepted fact, even without a mechanism of action.

6. Tooth wear

Image courtesy of Ernst Vikne, under Creative Commons license 

You may know what it means, but have you ever wondered where “don’t look a gift horse in the mouth” comes from? Back when gifts of livestock and work animals were common, horses were one of many grazing creatures exchanged. It was considered rude to look in its mouth, because your reason for doing so was to find out how old it was. The eruption and wear patterns on the teeth of many hooved animals are a good way to estimate age, and if you were looking to see how old the horse was, you were being ungrateful for having received the gift in the first place. Don’t ask how much a gift cost, don’t look a gift horse in the mouth, and be grateful for whatever you get—even if it’s a 25-year-old mare whose only use is as a grass trimmer!

7. Amino acid racemization

Antarctic Glaciers 

Living animals have lots of proteins in them. The proteins are made up of amino acids, and with very few exceptions, the bodies of creatures have developed in such a way that all of these amino acids are formed in a “left-facing” orientation. However, when left to their own devices, after a creature dies or a tissue becomes biologically inactive, the amino acids naturally fall into a racemic state—meaning there are equal amounts of left- and right-facing amino acids. The longer a tissue has been inactive, the closer to a 50:50 ratio the amino acids get. While there are many factors that affect how quickly this happens, once the rate of racemization is known, age at death or inactivation can be calculated.

Let's take a look at the inner eye of baleen whales, for example. The whale eye is formed in the womb, and grows by forming new tissue around the existing tissue—so the innermost layer is sort of like a tree core. The inner eye can show how old the creature is; one fin whale that was recently killed was found to have a harpoon from the early 19th century in its blubber, and by calculating the level of racemization of the inner eye, it was determined that it was highly plausible that the individual was an adult when it was first harpooned, and the artifact in its blubber probably wasn’t a fluke or a fake.

8. Carbon-14 decay

Today's Chemist 

While this technique is best known for finding how long it’s been since something died, and has been widely used in the fields of paleoanthropology, the biologically inactive tissues in animals that are used for amino acid dating also have a relatively known level of the radioactive isotope carbon-14. After a tissue becomes biologically inactive, the carbon-14 that’s incorporated into it will decay into the stable carbon-12 at a known rate. The ratio of carbon-14 to carbon-12 is then used to determine a timeline.

If it’s known how long ago something was alive (determined by tissues that are biologically active until death), the carbon-14 ratio in tissues that are biologically inactive after a certain age (such as parts of the adult teeth, after they erupt) can be compared to the time since death, to determine the probable age of an organism. Amino acid dating and carbon-14 dating are often used at the same time, to get a more accurate idea of the probable age at death or tissue inactivation.

9. Earwax plugs

Thinkstock

If you’ve ever had problems hearing because of earwax buildup, be grateful you’re not a blue whale! One of the most recently-developed methods of determining age is by taking the earwax “plug” out of a deceased baleen whale. Over its adult lifetime, the whale lays down alternating layers of light- and dark-colored earwax, correlating with its migration patterns and food sources. The earwax plug acts almost like a tree core, and each layer can be independently tested to determine if and when the whale consumed high levels of certain toxins, was physically stressed, or was exposed to radiation or other contaminants. The levels of pollutants and environmental toxins can show how long a certain pesticide, for example, stays in the oceans after it’s banned from use on land.

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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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Animals
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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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