Connect with us

The Conversation

African elephants address one another with name-like calls − similar to humans

Published

on

theconversation.com – Mickey Pardo, Postdoctoral Fellow in Fish, Wildlife and Conservation Biology, Colorado State University – 2024-06-11 12:47:10

Elephants have close social bonds, which may have led to the evolution of name-like calls.
Michael Pardo

Mickey Pardo, Colorado State University

What’s in a name? People use unique names to address each other, but we’re one of only a handful of animal species known to do that, including bottlenose dolphins. Finding more animals with names and investigating how they use them can improve scientists’ understanding of both other animals and ourselves.

As elephant researchers who have observed free-ranging elephants for years, my colleagues and I get to know wild elephants as individuals, and we make up names for them that help us remember who is who. The elephants in question live fully in the wild and are, of course, unaware of the epithets we apply to them.

But in a new study published in Nature Ecology and Evolution, we found evidence that elephants have their own names that they use to address each other. This research places elephants among the very small number of species known to address one another in this way, and it has implications for scientists’ understanding of animal intelligence and the evolutionary origins of language.

Finding evidence for name-like calls

My colleagues and I had long suspected that elephants might be able to address one another with name-like calls, but no researchers had tested that idea. To explore this question, we followed elephants across the Kenyan savanna, recording their vocalizations and noting, whenever possible, who made each call and whom the call was addressed to.

When most people think of elephant calls, they imagine loud trumpets. But really, most elephant calls are deep, thrumming sounds known as rumbles that are partially below the range of human hearing. We thought that if elephants have names, they most likely say them in rumbles, so we focused on these calls in our analysis.

Elephant rumbles have a deep, sonorous sound.
Michael Pardo236 KB (download)

We reasoned that if rumbles contain something like a name, then we should be able to identify whom a call is intended for based purely on the call’s properties. To determine whether this was the case, we trained a machine learning model to identify the recipient of each call.

We fed the model a series of numbers describing the sound properties of each call and told it which elephant each call was addressed to. Based on this information, the model tried to learn patterns in the calls associated with the identity of the recipient. Then, we asked the model to predict the recipient for a separate sample of calls. We used a total of 437 calls from 99 individual callers to train the model.

Part of the reason we needed to use machine learning for this analysis is because rumbles convey multiple messages at once, including the identity, age and sex of the caller, emotional state and behavioral context. Names are likely only one small component within these calls. A computer algorithm is often better than the human ear at detecting such complex and subtle patterns.

We didn’t expect elephants to use names in every call, but we had no way of knowing ahead of time which calls might contain a name. So, we included all the rumbles where we thought they might use names at least some of the time in this analysis.

The model successfully identified the recipient for 27.5% of these calls – significantly better than what it would have achieved by randomly guessing. This result indicated that some rumbles contained information that allowed the model to identify the intended recipient of the call.

But this result alone wasn’t enough evidence to conclude that the rumbles contained names. For example, the model might have picked up on the unique voice patterns of the caller and guessed who the recipient was based on whom the caller tended to address the most.

In our next analysis, we found that calls from the same caller to the same recipient were significantly more similar, on average, than calls from the same caller to different recipients. This meant that the calls really were specific to individual recipients, like a name.

Next, we wanted to determine whether elephants could perceive and respond to their names. To figure that out, we played 17 elephants a recording of a call that was originally addressed to them that we assumed contained their name. Then, on a separate day, we played them a recording of the same caller addressing someone else.

We played calls to the elephants in our sample, and some elephants called back.

The elephants vocalized and approached the source of the sound more readily when the call was one originally addressed to them. On average, they approached the speaker 128 seconds sooner, vocalized 87 seconds sooner and produced 2.3 times more vocalizations in response to a call that was intended for them. That result told us that elephants can determine whether a call was meant for them just by hearing the call out of context.

Names without imitation

Elephants are not the only animals with name-like calls. Bottlenose dolphins and some parrots address other individuals by imitating the signature call of the addressee, which is a unique “call sign” that dolphins and parrots usually use to announce their own identity.

This system of naming via imitation is a little different from the way names and other words typically work in human language. While we do occasionally name things by imitating the sounds that they make, such as “cuckoo” and “zipper,” most of our words are arbitrary. They have no inherent acoustic connection to the thing they refer to.

Arbitrary words are part of what allows us to talk about such a wide range of topics, including objects and ideas that don’t make any sound.

Intriguingly, we found that elephant calls addressed to a particular recipient were no more similar to the recipient’s calls than to the calls of other individuals. This finding suggested that like humans, but unlike other animals, elephants may address one another without just imitating the addressee’s calls.

Two elephants, and adult and a juvenile, stand together on a desert.
Elephants’ use of name-like calls underscores their intelligence.
Michael Pardo

What’s next

We’re still not sure exactly where the elephant names are located within a call or how to tease them apart from all of the other information conveyed in a rumble.

Next, we want to figure out how to isolate the names for specific individuals. Achieving that will allow us to address a range of other questions, such as whether different callers use the same name to address the same recipient, how elephants acquire their names, and even whether they ever talk about others in their absence.

Name-like calls in elephants could potentially tell researchers something about how human language evolved.

Most mammals, including our closest primate relatives, produce only a fixed set of vocalizations that are essentially preprogrammed into their brain at birth. But language depends on being able to learn new words.

So, before our ancestors could develop a full-fledged language, they needed to evolve the ability to learn new vocalizations. Dolphins, parrots and elephants have all independently evolved this capacity, and they all use it to address one another by name.

Maybe our ancestors originally evolved the ability to learn new vocalizations in order to learn names for each other, and then later co-opted this ability to learn a wider range of words.

Our findings also underscore how incredibly complex elephants are. Using arbitrary sounds to name other individuals implies a capacity for abstract thought, as it involves using sound as a symbol to represent another elephant.

The fact that elephants need to name each other in the first place highlights the importance of their many, distinct social bonds.

Learning about the elephant mind and its similarities to ours may also increase humans’ appreciation for elephants at a time when conflict with humans is one of the biggest threats to wild elephant survival.The Conversation

Mickey Pardo, Postdoctoral Fellow in Fish, Wildlife and Conservation Biology, Colorado State University

This article is republished from The Conversation under a Creative Commons license. Read the original article.

Read More

The post African elephants address one another with name-like calls − similar to humans appeared first on theconversation.com

The Conversation

From using plant rinds to high-tech materials, bike helmets have improved significantly over the past 2 centuries

Published

on

theconversation.com – Jud Ready, Principal Research Engineer in Materials Science and Engineering, Georgia Institute of Technology – 2024-11-18 07:27:00

Modern bike helmets are made through complex materials engineering.
Johner Images via Getty Images

Jud Ready, Georgia Institute of Technology

Imagine – it’s the mid-1800s, and you’re riding your high-wheeled, penny-farthing bicycle down a dusty road. Sure, it may have some bumps, but if you lose your balance, you’re landing on a relatively soft dirt road. But as the years go by, these roads are replaced with pavement, cobblestones, bricks or wooden slats. All these materials are much harder and still quite bumpy.

As paved roads grew more common across the U.S. and Europe, bicyclists started to suffer gruesome skull fractures and other serious head injuries during falls.

As head injuries became more common, people started seeking out head protection. But the first bike helmets were very different than helmets of today.

I’m a materials engineer who teaches a course at Georgia Tech about materials science and engineering in sports. The class covers many topics, but particularly helmets, as they’re used in many different sports, including cycling, and the materials they’re made of play an important role in how they work. Over the decades, people have used a wide variety of materials to protect their heads while biking, and companies continue to develop new and innovative materials.

In the beginning, there was the pith helmet.

Pith helmets

The first head protection concept introduced to the biking world was a hat made from pith, which is the spongy rind found in the stem of sola plants, aeschynomene aspera. Pith helmet craftsmen would press the pith into sheets and laminate it across dome-shaped molds to form a helmet shape. Then, they’d cover the hats in canvas as a form of weatherproofing.

A hat made of a brown material with a flat rim.
Hats made out of pith were used by militaries as well as for head protection while biking.
Auckland Museum, CC BY-SA

Pith helmets were far from what we would consider a helmet today, but they persisted until the early 20th century, when bicycle-racing clubs emerged. Since pith helmets offered little to no ventilation, the racers began to use halo-shaped leather helmets. These had better airflow and were more comfortable, although they weren’t much better at protecting the head.

A bike helmet made from leather strips connected into a dome on the head of a mannequin.
Leather strip bike helmets were made in the 1930s.
Museums Victoria, CC BY-SA

Leather halo helmets

The initial concept for the halo helmet used a simple leather strip wrapped around the forehead. But these halo helmets quickly evolved, as riders arranged additional strips longitudinally from front to back. They wrapped the leather bands in wool.

For better head protection, the helmet makers then started adding more layers of leather strips to increase the helmet’s thickness. Eventually, they added different materials such as cotton, foam and other textiles into these leather layers for better protection.

While these had better airflow than the pith hats, the leather “hairnet” helmets continued to offer very little protection during a fall on a paved surface. And, like pith, the leather helmets degraded when exposed to sweat and rain.

Despite these drawbacks, leather strip helmets dominated the market for several decades as cycling continued to evolve throughout the 20th century.

Then, in the 1970s, a nonprofit dedicated to testing motorcycle helmets called the Snell Foundation released new standards for bike helmets. They set their standards so high that only lightweight motorcycle helmets could pass, which most bicyclists refused to wear.

New materials and new helmets

The motorcycle equipment manufacturing company Bell Motorsports responded to the new standards by releasing the Bell Biker in 1975. This helmet used expanded polystyrene, or EPS. EPS is the same foam used to manufacture styrofoam coolers. It’s lightweight and absorbs energy well.

Constructing the Bell Biker involved spraying EPS into a dome shaped mold. The manufacturers used small pellets of a very hard plastic – polycarbonate, or PC – to mold an outer shell and then adhere it to the outside of the EPS.

Mottled white foam
Expanded polystyrene, or EPS, is a foam used in styrofoam coolers as well as the core of bike helmets.
Tiia Monto/Wikimedia Commons, CC BY-SA

Unlike the pith and leather helmets, this design was lightweight, load bearing, impact absorbing and well ventilated. The PC shell provided a smooth surface so that during a fall, the helmet would skid along the pavement instead of getting jerked around and caught, which could cause abrupt head rotation and lead to concussions and other head and neck injuries.

Over the next two decades, as cycling became more popular, helmet manufacturers tried to strike the perfect balance between lightweight and ventilated helmets, while simultaneously providing impact protection.

In order to decrease weight, a company called Giro Sport Design created an all-EPS helmet covered by a thin lycra fabric cover instead of a hard PC shell. This design eliminated the weight of the PC shell and improved ventilation.

In 1989, a company called Pro Tec introduced a helmet with a nylon mesh infused in the EPS foam core. The nylon mesh dramatically increased the helmet’s structural support without the added weight of the PC shell.

A man standing by a bike wearing a green helmet that's made of a thin material with a long tail.
Many racing cyclists found teardrop-style helmets to be more aerodynamic.
Bongarts/Getty Images, CC BY-NC-ND

Meanwhile, as cycling became more competitive, many riders and manufacturers started designing more aerodynamic helmets using the existing materials. A revolutionary teardrop style helmet debuted in the 1984 Olympics.

Now, even casual biking enthusiasts will don teardrop helmets.

Helmets on the market today

Helmet makers continue to innovate. Today, many commercial brands use a hard polyethylene terephthalate, or PET, shell around the EPS foam in place of a PC shell to increase the helmet’s protection and lifespan, while decreasing cost.

Meanwhile, some brands still use PC shells. Instead of gluing them to the EPS foam, the shell serves as the mold itself, with the EPS expanding to fit inside it. Manufacturing helmets this way eliminates several process steps, as well as any gaps between the foam and shell. This process makes the helmet both stronger and cheaper to manufacture.

As helmets evolve to provide more protection with still lighter weight, materials called copolymers, such as acrylonitrile-butadiene-styrene, are replacing PC and PET shell materials.

Materials that are easier and cheaper to manufacture, such as expanded polyurethane and expanded polypropylene, are also starting to replace the ubiquitous EPS core.

Just as the leather and pith helmets would look strange to a cyclist today, a century from now, bike helmets could be made with entirely new and innovative materials.The Conversation

Jud Ready, Principal Research Engineer in Materials Science and Engineering, Georgia Institute of Technology

This article is republished from The Conversation under a Creative Commons license. Read the original article.

Read More

The post From using plant rinds to high-tech materials, bike helmets have improved significantly over the past 2 centuries appeared first on theconversation.com

Continue Reading

The Conversation

Why the Justice Department is suing a software company to stop landlords colluding on rents

Published

on

theconversation.com – Roger Alford, Professor of Law, University of Notre Dame – 2024-11-18 07:27:00

Landlords don’t have to communicate directly to collude on rental prices.
AP Photo/Gene J. Puskar

Roger Alford, University of Notre Dame

Of all the reasons it could be hard to pay rent each month, did you have an algorithm-powered illegal cartel on your list?

Millions of people across the United States are paying far more rent than they can reasonably afford, with rental housing prices rising far quicker than household income. In 2022, 22.4 million U.S. households were spending more than 30% of their income on rent and utilities, up from 20.4 million in 2019.

Many of these households faced severe cost burdens, with an all-time high of 11.6 million struggling with housing costs that consume more than half of their income. In Chicago, Cincinnati, Minneapolis, Virginia Beach and Washington, year-over-year rental prices are climbing at double-digit rates.

Several factors drive the high cost of rentals, including increasing demand, a dwindling supply of low-rent units, the rising cost of capital to build new rentals, and regulatory barriers restricting the construction of multifamily units.

But there’s another surprising factor driving up rental prices: landlords colluding with the help of technology. The U.S. Justice Department is suing the company RealPage, Inc., accusing it of selling software to landlords that allows them to collectively set prices – the illegal practice of price-fixing. As a former official in the Justice Department’s Antitrust Division and a law professor, I’ve been following the case closely.

The perils of price-fixing

The Federal Trade Commission defines price-fixing as an agreement, conspiracy or combination among competitors to raise, fix or otherwise maintain the price at which their goods or services are sold.

Any agreement that restricts price competition violates the antitrust laws. Examples of price-fixing agreements include commitments among competitors to hold prices firm, adopt a standard formula for computing prices, or adhere to a minimum fee or price schedule.

So when competitors share proprietary, confidential current price information – directly or indirectly through an intermediary – to stabilize or control industry pricing, they have crossed the line into illegal collusion, according to the FTC. That is the case in major portions of the U.S. rental market, the Justice Department argues.

One algorithm for all

In August 2024, the Justice Department and eight states filed a lawsuit in a federal court in North Carolina against RealPage. The Justice Department accused the company of selling software to landlords that collects nonpublic information from competing landlords and uses that combined information to make pricing recommendations.

two men and a woman in business attire stand behind a lectern and in front of flags and a logo
Attorney General Merrick Garland, Deputy Attorney General Lisa Monaco and Acting Associate Attorney General Benjamin Mizer at a news conference about the Justice Department suing RealPage on Aug. 23, 2024.
AP Photo/Mark Schiefelbein

Landlords who use the software input the rental prices they charge, and the software aggregates all the data from the company’s customers. The software’s algorithm then makes recommendations for what to charge. The recommendations are generally higher than the current market rate, and most customers take the recommendations, which push prices in a market higher.

Even if landlords retain some authority to deviate from the algorithm’s recommendations, it is illegal for competing landlords to jointly delegate key aspects of their pricing to a common algorithm, according to the Justice Department suit. The Justice Department declared that “RealPage replaces competition with coordination. It substitutes unity for rivalry. It subverts competition and the competitive process. It does so openly and directly – and American renters are left paying the price.”

The case is unusual in that, unlike a typical price-fixing cartel, the landlords used RealPage’s algorithms to dramatically improve their ability to engage in price-fixing. Algorithmic price-fixing is typically easier and more effective than other types of cartel behavior. The software can easily aggregate massive amounts of proprietary data, optimize cartel gains, monitor real-time deviations from cartel pricing and minimize incentives to cheat.

“It’s much easier to price-fix when you’re outsourcing it to an algorithm versus when you’re sharing manila envelopes in a smoke-filled room,” Justice Department antitrust chief Jonathan Kanter told The New York Times.

Since 2022, RealPage and various property managers have been named as defendants in more than 30 class action lawsuits alleging the RealPage software is used to unlawfully fix rental prices. Federal courts tend to be sympathetic to such arguments, as shown in the denial of a motion to dismiss the case in one of the private lawsuits filed against RealPage.

In that case, the court held that a price-fixing agreement could exist as a matter of law. Landlords provided RealPage’s algorithmic system with their proprietary commercial data, knowing that RealPage would require the same from their competitors and would use all of that data to recommend rental prices to all of the company’s clients.

A news report summarizes the government’s case against RealPage.

Classic price-fixing or data-driven decisions?

Some landlords seem to be aware that in sharing confidential price information to RealPage’s software, they were facilitating the unlawful monitoring and raising of rental prices. The Justice Department complaint quoted a landlord commenting on RealPage’s software, “I always liked this product because your algorithm uses proprietary data from other subscribers to suggest rents and term. That’s classic price-fixing.”

Even RealPage’s own executives have boasted that when landlords collectively use their software, they can use “every possible opportunity to increase price,” according to the complaint.

RealPage argued that its software “simply helps landlords make data-driven decisions” in a competitive market. The company claims its tools are designed to reflect market conditions and optimize occupancy rates, not to engage in price-fixing.

The company describes the impact of its alleged collusion with landlords as “a rising tide [that] raises all ships.” Perhaps a better description for their service is a rising tide that raises all ships for those who have one.

The Justice Department’s case and the private cases are in the early stages of litigation. If the department is successful, RealPage will be barred from engaging in the anticompetitive practices related to helping landlords share proprietary pricing information.The Conversation

Roger Alford, Professor of Law, University of Notre Dame

This article is republished from The Conversation under a Creative Commons license. Read the original article.

Read More

The post Why the Justice Department is suing a software company to stop landlords colluding on rents appeared first on theconversation.com

Continue Reading

The Conversation

Why do I feel better when I wake myself up instead of relying on an alarm? A neurologist explains the science of a restful night’s sleep

Published

on

theconversation.com – Beth Ann Malow, Professor of Neurology and Pediatrics, Vanderbilt University – 2024-11-18 07:25:00

Your internal body clock can help wake you up without an alarm.

Riska/E+ via Getty Images

Beth Ann Malow, Vanderbilt University

Curious Kids is a series for children of all ages. If you have a question you’d like an expert to answer, send it to curiouskidsus@theconversation.com.


Why do I feel better rested when I wake myself up than I do if my alarm or another person wakes me up? – Calleigh H., age 11, Oklahoma


We’ve all experienced this: You’re in the middle of a lovely dream. Perhaps you’re flying. As you’re soaring through the air, you meet an eagle. The eagle looks at you, opens its beak and – BEEP! BEEP! BEEP!

Your alarm goes off. Dream over, time to get up.

Many people – kids and adults alike – notice that when they wake up naturally from sleep, they feel more alert than if an alarm or another person, like a parent, wakes them up. Why is that?

I’m a neurologist who studies the brain, specifically what happens in the brain when you’re asleep. I also take care of children and adults who don’t sleep well and want to sleep better. My research involves working with parents to help them teach their children good sleep habits.

To understand how to sleep better, and why waking up naturally from sleep helps you feel more alert, you need to start by understanding sleep cycles.

The sleep cycle

The sleep cycle consists of four stages. One of these is REM, which stands for rapid eye movements. The other three are non-REM stages. When you fall asleep, you first go into a state of drowsiness called non-REM Stage 1.

This is followed by deeper stages of sleep, called non-REM stages 2 and 3. Each stage of non-REM is deeper than the one before. Then, about 90 minutes after you first fall asleep, you enter the fourth stage, which is REM sleep. This is a stage of lighter sleep where you do much of your dreaming. After a few minutes, you return to non-REM sleep again.

Segments of a circle indicate the four stages of the sleep cycle: Non-REM 1, Non-REM 2, Non-REM 3, and REM.

The four stages of the sleep cycle.

The Conversation, CC BY

These cycles repeat themselves throughout the night, with most people having four to six cycles of non-REM sleep alternating with REM sleep each night. As the night goes on, the cycles contain less non-REM sleep and more REM sleep. This is why it’s important to get enough sleep, so that the body can get enough of both REM sleep and non-REM sleep.

REM vs. non-REM sleep

How do researchers like me know that a person is in non-REM vs. REM sleep? In the sleep lab, we can tell from their brain waves, eye movements and the tension in their muscles, like in the chin. These are measured by putting sensors called electrodes on the scalp, around the eyes and on the chin.

These electrodes pick up brain activity, which varies from waves that are low in amplitude (the height of the wave) and relatively fast to waves that are high in amplitude (a taller wave) and relatively slow. When we are awake, the height of the waves is low and the waves are relatively fast. In contrast, during sleep, the waves get higher and slower.

Non-REM Stage 3 has the tallest and slowest waves of all the sleep stages. In REM sleep, brain waves are low in amplitude and relatively fast, and the eye movements are rapid, too. People need both non-REM and REM stages for a healthy brain, so they can learn and remember.

Waking up naturally

When you wake up in the morning on your own, it’s usually as you come to the end of whatever stage of sleep you were in. Think of it like getting off the train when it comes to a stop at the station. But when an alarm or someone else wakes you up, it’s like jumping off the train between stops, which can feel jolting. That’s why it’s good to wake up naturally whenever possible.

People can actually train their brains to wake up at a consistent time each day that is a natural stopping point. Brains have an internal 24-hour clock that dictates when you first start to feel sleepy and when you wake up. This is related to our circadian rhythms.

You can adjust your circadian rhythm so that you wake naturally each morning.

Training the brain to wake up at a consistent time

First, it’s important to go to bed at a consistent time that allows you to get enough sleep. If you stay up too late doing homework or looking at your phone, that can interfere with getting enough sleep and make you dependent on an alarm – or your parents – to wake you up.

Other things that can help you fall asleep at a healthy time include getting physical activity during the day and avoiding coffee, soda or other drinks or foods that contain caffeine. Physical activity increases brain chemicals that make it easier to fall asleep, while caffeine does the opposite and keeps you awake.

Second, you need to be aware of light in your environment. Light too late in the evening, including from screens, can interfere with your brain’s production of a chemical called melatonin that promotes sleep. But in the morning when you wake up, you need to be exposed to light.

Morning light helps you synchronize, or align, your circadian rhythms with the outside world and makes it easier to fall asleep at night. The easiest way to do this is to open up your shades or curtains in your room. In the winter, some people use light boxes to simulate sunlight, which helps them align their rhythms.

Benefits of a good night’s sleep

A good sleep routine entails both a consistent bedtime and wake time and regularly getting enough sleep. That usually means 9-11 hours for school-age kids who are not yet teens, and 8-10 hours for teens.

This will help you be at your best to learn at school, boost your mood, help you maintain a healthy weight and promote many other aspects of health.


Hello, curious kids! Do you have a question you’d like an expert to answer? Ask an adult to send your question to CuriousKidsUS@theconversation.com. Please tell us your name, age and the city where you live.

And since curiosity has no age limit – adults, let us know what you’re wondering, too. We won’t be able to answer every question, but we will do our best.The Conversation

Beth Ann Malow, Professor of Neurology and Pediatrics, Vanderbilt University

This article is republished from The Conversation under a Creative Commons license. Read the original article.

Read More

The post Why do I feel better when I wake myself up instead of relying on an alarm? A neurologist explains the science of a restful night’s sleep appeared first on theconversation.com

Continue Reading

Trending