That finding comes from a study published today in the journal Science Advances and led by Scott Ortman, an archaeologist at the University of Colorado Boulder. He’s one of a growing number of antiquarians who argue that the world’s past may hold the key to its future. What lessons can people living today take from the successes and failures of civilizations hundreds or thousands of years ago?

Recently, Ortman and Jose Lobo from Arizona State University took a deep dive into data from the farming towns that dotted the Rio Grande Valley between the 14th and 16th centuries. Modern metropolises should take note: As the Pueblo villages grew bigger and denser, their per capita production of food and other goods seemed to go up, too.

Busy streets, in other words, may lead to better-off citizens.

“We see an increasing return to scale,” said Ortman, an assistant professor in the Department of Anthropology who is also affiliated with the Santa Fe Institute in New Mexico. “The more people work together, the more they produce per person.”

Whether the same thing is true today remains an open question, especially amid the unprecedented impacts of the COVID-19 pandemic on cities and human proximity. But the results from the sunny Southwest suggest that it’s an idea worth exploring.

“The archaeological record can help us to learn about issues we care about today in ways that we can’t do using the data available to us from modern societies,” Ortman said.

The good dishes

The research is an offshoot of an effort that Ortman leads called the Social Reactors Project, which has explored patterns of growth in civilizations from ancient Rome to the Incan world.

It’s an attempt to chase down an idea first proposed in the 18th century by Adam Smith, often known as the father of modern economics. In The Wealth of Nations, Smith made the case for the fundamental benefits of market size — that if you make it easier for more people to trade, the economy will grow.

Just look at any city in the U.S. where you might find a hair salon next to a bakery next to a doggie daycare.

“As people interact more frequently, a person can make and do fewer things themselves and get more of what they need from their social contacts,” Ortman said.

The problem, he explained, is that such “agglomeration-driven” growth is difficult to isolate in today’s big and complex cities. The same isn’t true for the Rio Grande Valley.

Before the arrival of the Spaniards in the 16th century, hundreds of villages spanned the region near what is now Santa Fe. These settlements ranged in size from a few dozen residents to as many as 3,000 people, most of whom made their living by growing crops like maize and cotton.

Such a subsistence lifestyle didn’t mean that these communities were simple.

“The traditional view in ancient history was that economic growth didn’t happen until the onset of the industrial revolution,” Ortman said.

He and Lobo decided to put that assumption to the test. The duo pored through an exhaustive database of archaeological finds from the region — capturing everything from the number and size of rooms in Pueblo communities to the pottery from rubbish heaps.

They unearthed a clear trend: When villages got more populous, their residents seemed to get better off on average — exactly as Smith predicted. Living spaces grew in size and families collected more painted pottery.

“You might think of it as more sets of dishes for sharing meals together,” Ortman said.

Social connection

That growth, the team discovered, also seemed to follow a pattern that researchers on the Social Reactors Project have seen in a range of civilizations throughout history. Every time villages doubled in size, markers of economic growth increased by about 16% on average.

Ortman said that the effect doesn’t happen in the same way everywhere. Factors like inequality and racism, for example, can keep urban residents from working together even when they live in cramped spaces.

But, Ortman added, these Pueblo communities hold an important lesson for modern-day societies: the more people can connect with others, the more prosperous they become.

“All other things being equal, urbanization should lead to improvements in the material conditions of life for people everywhere,” he said. “We suspect this is why the world continues to urbanize, despite all of the associated problems.”

Among astronomers, it has long been well-established that most galaxies host a black hole at their center. But galaxies hosting a pair of black holes has remained theoretical.

The results of the team’s research appeared in The Astrophysical Journal on June 19, 2020 in a paper titled “Systematic search for gamma-ray periodicity in active galactic nuclei detected by the Fermi Large Area Telescope.”

“In general, supermassive black holes are characterized by masses of more than a million masses of that of our sun,” said Pablo Peñil, lead author of the study and a Ph.D. student at Universidad Complutense de Madrid in Spain. “Some of these supermassive black holes, known as active galactic nuclei (AGN) have been found to accelerate particles to near the speed of light in collimated beams called jets. The emission from these jets is detected throughout the entire electromagnetic spectrum, but most of their energy is released in the form of gamma rays.”

Gamma rays, which are the most extreme form of light, are detected by the Large Area Telescope onboard NASA’s Fermi Gamma-ray Space Telescope. AGN are characterized by abrupt and unpredictable variations in brightness.

“Identifying regular patterns in their gamma-ray emission is like looking at the stormy sea and searching for the tiny regular set of waves caused by, say, the passage of a small boat,” Peñil said. “It becomes very challenging very quickly.”

The team accomplished the first difficult step of identifying a large number of galaxies that emits periodically over years and is trying to address the question of what is producing that periodic behavior in these AGN. Several of the potential explanations are fascinating.

“The next step will be the preparation of observational campaigns with other telescopes to closely follow up on these galaxies and hopefully unravel the reasons behind these compelling observations,” said co-author Marco Ajello, an associate professor in the College of Science’s department of physics and astronomy at Clemson University. “We have a few possibilities in mind — from lighthouse effects produced by the jets to modulations in the flow of matter to the black hole — but one very interesting solution would be that periodicity is produced by a pair of supermassive black holes rotating around each other. Understanding the relation of these black holes with their environment will be essential for a complete picture of galaxy formation.”

Thanks to a decade of Fermi-LAT observations, the team was able to identify the repetition of gamma-ray signals over cycles of a few years. On average, these emissions repeated about every two years.

“Our study represents the most complete work to date on the search for periodicity in gamma rays, a study that will be instrumental in deriving insights about the origin of this peculiar behavior,” said co-author Alberto Domínguez, Peñil’s Ph.D. supervisor in Madrid and also a former postdoctoral researcher in Ajello’s group at Clemson. “We have used nine years of continuous LAT all-sky observations. Among the more than two thousand AGN analyzed, only about a dozen stand out for this intriguing cyclical emission.”

Enlarging the limited sample of periodic emitters constitutes an important leap forward for understanding the underlying physical processes in these galaxies.

“Previously only two blazars were known to show periodic changes in their gamma-ray brightness. Thanks to our study, we can confidently say that this behavior is present in 11 other sources,” said co-author Sara Buson, a professor at University of Würzburg in Germany. “In addition, our study found 13 other galaxies with hints of cyclical emission. But to confidently confirm this, we need to wait for Fermi-LAT to collect even more data.”

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Previous research has identified several ways in which echolocation can transfer social information in bats. For example, “feeding buzzes,” the echolocation calls bats produce to home in on prey they’ve spotted, can serve as cues of prey presence to nearby eavesdropping bats. On the other hand, echolocation calls that bats produce while looking for food, called “search-phase” calls, were not known to transfer social information.

However, for group-foraging bats, coordinating flight in the dark with several other fast-flying individuals may require an ability to identify group members on the wing. If search-phase calls contain individual signatures the bats can perceive, it could allow them to know which individuals are flying near them without requiring specialized signals for communication.

Led by Jenna Kohles, STRI fellow and doctoral candidate at the Max Planck Institute of Animal Behavior in Germany, the research team tested whether search-phase echolocation calls contain information about a bat’s identity, and whether M. molossus can use this information to discriminate among different group members. The team exposed bats to search-phase echolocation calls in a habituation-dishabituation paradigm, a method where an animal is exposed to a repeating stimulus until it no longer reacts to it. Then, it is exposed to a new but similar stimulus to see if it reacts, which would indicate that it perceives a difference between the two stimuli.

“We played echolocation calls from two different bats that were both group members of the subject bat,” Kohles said. “By measuring the responses of the subject bats as we switched between calls from different individuals, we could learn about whether the bats perceived differences and similarities between the calls.”

They found that the bats indeed distinguish between different group members, likely by using individual signatures encoded in the calls. Their results could mean that search-phase calls serve a double function. They not only help bats detect prey, but also convey individual identities to nearby foraging group members. This coincides with the fact that the majority of M. molossus’ auditory cortex is tuned in to these search-phase calls, indicating the importance of processing them.

This finding offers insight into not only the social strategies these bats may use to meet their energetic needs, but also into the evolution of echolocation signals and social communication in bats.

“This study suggests that we may be underestimating the crucial ways social information influences bat foraging success and ultimately survival,” Kohles said.

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Neural networks are an advanced type of AI loosely based on the way that our brains work. Our natural neurons exchange electrical impulses according to the strengths of their connections. Artificial neural networks mimic this behavior by adjusting numerical weights and biases during training sessions to minimize the difference between their actual and desired outputs. For example, a neural network can be trained to identify photos of dogs by sifting through a large number of photos, making a guess about whether the photo is of a dog, seeing how far off it is and then adjusting its weights and biases until they are closer to reality.

The drawback to this neural network training is something called “chaos blindness” — an inability to predict or respond to chaos in a system. Conventional AI is chaos blind. But researchers from NC State’s Nonlinear Artificial Intelligence Laboratory (NAIL) have found that incorporating a Hamiltonian function into neural networks better enables them to “see” chaos within a system and adapt accordingly.

Simply put, the Hamiltonian embodies the complete information about a dynamic physical system — the total amount of all the energies present, kinetic and potential. Picture a swinging pendulum, moving back and forth in space over time. Now look at a snapshot of that pendulum. The snapshot cannot tell you where that pendulum is in its arc or where it is going next. Conventional neural networks operate from a snapshot of the pendulum. Neural networks familiar with the Hamiltonian flow understand the entirety of the pendulum’s movement — where it is, where it will or could be, and the energies involved in its movement.

In a proof-of-concept project, the NAIL team incorporated Hamiltonian structure into neural networks, then applied them to a known model of stellar and molecular dynamics called the Hénon-Heiles model. The Hamiltonian neural network accurately predicted the dynamics of the system, even as it moved between order and chaos.

“The Hamiltonian is really the ‘special sauce’ that gives neural networks the ability to learn order and chaos,” says John Lindner, visiting researcher at NAIL, professor of physics at The College of Wooster and corresponding author of a paper describing the work. “With the Hamiltonian, the neural network understands underlying dynamics in a way that a conventional network cannot. This is a first step toward physics-savvy neural networks that could help us solve hard problems.”

The work appears in Physical Review E and is supported in part by the Office of Naval Research (grant N00014-16-1-3066). NC State postdoctoral researcher Anshul Choudhary is first author. Bill Ditto, professor of physics at NC State, is director of NAIL. Visiting researcher Scott Miller; Sudeshna Sinha, from the Indian Institute of Science Education and Research Mohali; and NC State graduate student Elliott Holliday also contributed to the work.

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“I’ve been doing work on the costs of wind farms for about 10 years and I’ve found that the soft costs — basically the cost interactions between people — are overlooked,” said Erin MacDonald, assistant professor of mechanical engineering at Stanford. “Existing models can tell us how to eke out a little more value by making a blade turn in a slightly different way but aren’t focused on the reasons why a community accepts or rejects a wind farm.”

In a paper, published June 19 in the Journal of Mechanical Design, the researchers present a model that highlights three actions developers could take during this process of landowner acquisition — community engagement meetings, preliminary environmental studies and sharing plans for wind turbine layout with the landowner — and investigates how those actions would affect the eventual cost of the wind farm. The cost analysis suggests that these actions, while contributing to upfront costs, may end up saving developers money in the long run.

With additional input from real-life landowner acquisition case studies, the researchers hope to further refine this model to ultimately increase the success of project implementation and reduce the cost of overall wind farm development.

Quantifying interactions

During the process of planning a wind farm, a developer uses models to predict how much the project will cost versus how much energy it will produce. These models are mathematical formulas that map the relationships between different pieces of a project — such as materials, labor, land and, in this case, interactions between developers and landowners.

In previous work, MacDonald and her former graduate student and postdoctoral fellow, Le Chen, created a model where they integrated landowner decision-making into a wind farm layout optimization model — which otherwise focuses on what physical layout will produce the most energy. With this model, developers can anticipate and prioritize which landowners will have the most influence on the success of their project. This latest work adds details about other interpersonal interactions throughout the early development process.

“When I worked in the energy industry, the models I used often lacked human input,” said Sita Syal, a graduate student in mechanical engineering and lead author of the paper. “We don’t deny the rigor of economic or engineering analysis, but we encourage developers to consider the benefits of social analysis as well.”

“This work gives developers a framework to evaluate different actions, whereas right now it’s hard to compare potential impacts of those actions, for example, how investing in landowner relations stacks up against buying more efficient equipment,” said Yiqing Ding, a graduate student in mechanical engineering and co-author of the paper.

To account for soft costs in their model, the researchers had to study and brainstorm different scenarios for the interactions that occur during wind farm development — and their outcomes — and then translate the most crucial details of those interactions into formulas that could integrate with more traditional project analysis models. Their model, which is an initial proof-of-concept, suggests that actions that increase landowner involvement in the planning process lead to more landowners accepting a development contract, and this increase in acceptance would translate to cost savings overall — particularly in cases where they prevent failure of the project.

“The model suggests that taking preemptive actions can improve landowners’ acceptance but can also incur cost,” said Ding. “Timing is also important: we found that when an action is taken can influence landowner acceptance.”

While some developers conduct community meetings and preliminary environmental studies, sharing a layout plan with landowners is rare. Typically, all landowners involved in a wind farm will be given a vague contract that does not actually specify how their land will be used by the final project and, relatedly, how much money they will be paid.

A co-design process

The researchers recognize that making the development process more transparent is challenging and adds to initial expenses. However, they are still optimistic about the potential for innovative, collaborative actions that could ultimately improve the success and value of wind power.

For example, MacDonald suggests that virtual reality mockups of turbine plans might increase landowner contract acceptance, given that previous studies have found that people tend to be more accepting of the appearance of turbines once they see them in place.

“It would almost be like a co-design process between the developers and landowners,” said MacDonald. “The developer is including the landowner in the process in a collaborative way by showing them, not just where the turbines would be, but also explaining the advantages and disadvantages of different layouts.”

Other options for increasing transparency and collaboration could include making contracts easier to read and giving landowners some choice, such as two alternatives for how their land could be used.

Meanwhile, the proof-of-concept model for landowner acceptance requires continued research and refinement. The researchers are hoping to see more studies of soft costs for wind farms in general and would like to gain more insight into developers’ processes — which tend to be proprietary — in order to make the model useful to them.

The best outcome would be that all their painstaking efforts to distill and translate human interaction into mathematical relationships result in a program where a developer could, for example, input the amount of money they plan to spend on community meetings and receive a probability for landowner contracts that is customized to that community.

“We’re thinking many steps down the line but someday this could be a tool for creating community-supported sustainable energy infrastructure,” said Syal.

In the process, they made an unexpected discovery: myosin, one of the three main proteins that make up striated muscle fibers, appears to enter the Z-disc. Models of how myosin, actin and the elastic scaffold protein titin work together have largely ignored the possibility that myosin filaments penetrate the Z-disc structure. Only recently have German scientists theorized that they do, but no experimental evidence has validated the model, until now.

“This is going to be unexpected even for myosin researchers,” says Professor Michael Gotthardt, who heads MDC’s Neuromuscular and Cardiovascular Cell Biology Lab and led the research. “It gets to the very basics of how muscles generate force.”

Who’s there?

Gotthardt’s team including first authors Dr. Franziska Rudolph and Dr. Claudia Fink with the help from colleagues at the MDC and the University of Göttingen, never set out to validate this theory. Their primary goal was to identify the proteins in and near the Z-disc. To do this, they developed a mouse model with an artificial enzyme, called BioID, inserted into the giant protein titin. The Titin-BioID then tagged proteins close to the Z-disc.

Sarcomeres are tiny molecular machines, packed with proteins that tightly interact. Until now it has been impossible to separate proteins specific to the different subregions, especially in live, functioning muscle. “Titin-BioID probes specific regions of the sarcomere structure in vivo,” says Dr. Philipp Mertins, who heads MDC’s Proteomics Lab. “This has not been possible before.”

The team is the first to use BioID in live animals under physiological conditions and identified 450 proteins associated with the sarcomere, of which about half were already known. They found striking differences between heart and skeletal muscle, and adult versus neonatal mice, which relate to sarcomere structure, signaling and metabolism. These differences reflect the need of adult tissue to optimize performance and energy production versus growth and remodeling in neonatal tissue.

“We wanted to know who’s there, know who the players are,” Gotthardt says. “Most were expected, validating our approach.”

The surprise

The protein that they were not expecting to see in the Z-disc was myosin, which is integrated at the opposite site of the sarcomere. When a muscle is triggered to move, myosin walks along actin bringing neighboring Z-discs closer together. This sliding of actin and myosin filaments creates the force that enables our heart to pump blood or our skeletal muscle to maintain posture, or lift an object.

This so-called “sliding filament model” of the sarcomere describes force production and helps explain how force and sarcomere length relate. However, current models have trouble predicting the behavior of fully contracted sarcomeres. Those models have assumed myosin does not enter the Z-disc on its walk along actin. There have been some hints that maybe it keeps going. “But we didn’t know if what we were seeing in stained tissue samples was an artefact or real life,” Gotthardt says. “With BioID we can sit at the Z-disc and watch myosin pass by.”

Gotthardt agrees with the proposed theory that myosin entering the Z-disc can limit or dampen the contraction. This might help solve the ongoing issue scientists have had calculating how much force a muscle fiber can create in relation to its length and lead to a refined model of the sarcomere and possibly serve to protect muscle from excessive contraction.

Why it matters

Understanding how muscle fibers extend and contract on the molecular level under normal conditions is important so researchers can then identify what is going wrong when muscles are damaged, diseased or atrophy with age. Identifying which proteins are causing problems could potentially help identify novel treatment targets for patients with heart disease or skeletal muscle disorders.

Gotthardt and his team plan to next use BioID to study animals with different pathologies, to see what proteins are involved in muscle atrophy, for example. “Maybe a protein that is not normally there goes into the sarcomere, and it is part of the pathology,” Gotthardt says. “We can find it with BioID.”

A new paper by University of Illinois at Urbana-Champaign geology and geography professor Jim Best and University of Southampton professor Stephen Darby takes a big-picture approach to review the health and resiliency of the world’s large river systems, their deltas and their vulnerability to extreme events.

The article is published in the journal One Earth.

Rivers respond to changes in the environment through self-adjusting processes of erosion and sedimentation, the researchers said. When not stressed by extreme events like flooding or drought, these responses typically allow rivers to absorb change. However, data from many new studies now suggest that the world’s great waterways are becoming more vulnerable as the effects of human activity and climate change combine and compound.

“Climate change is of huge importance in terms of changing flood or drought frequency and intensity,” Best said. “However, there is a range of other stressors affecting big rivers such as damming, sediment mining, pollution, water diversions, groundwater extraction and the introduction of nonnative species — all of which affect rivers on a timescale that has much more immediate consequences.”

For example, the team reviewed past research on the drivers of flooding in the Mekong River Delta in Southeast Asia, which supports about 18 million people and a vast rice agricultural area. These studies suggest that delta subsidence — or sinking — because of groundwater extraction beneath the delta is now more of a problem, as the region receives far less sediment because of sediment trapping behind upstream dams and large-scale mining of sand from the bed of the delta’s channels.

“The scale of the effects of sediment starvation and subsidence in driving increased flood risk is currently far greater than sea-level rise generated by global climate change,” Best said. “But when all of these pressures are combined, there is now a real risk that we could cross a major tipping point in the next 10-20 years.”

Politics also play a significant role in the health and resiliency of the world’s major river systems, the paper reports. For example, the current COVID-19 pandemic is influencing regulatory enforcement of pollution monitoring in the United States, enabling polluters to avoid penalties if they argue violations are a result of the pandemic.

“We have seen evidence of the effect of these types of political and societal shocks on river systems in the past, too,” Best said. “The stresses from the Gulf War led to increased river pollution in the Tigris-Euphrates River Basin, a situation that was also compounded by upstream damming in Turkey.”

The researchers stress an urgent need for governance at the local level across to the international level to confront these issues effectively.

“There are some things we as scientists can do on the monitoring end of this issue, but it will demand collaboration and trust between nations for it to make a difference,” Best said. “We can’t take our eye off the ball — we’ve just got to devote more attention to these more frequent, shorter-timescale stressors. It’s far from being just about climate change.”

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