For something so fundamental to our existence, mate selection remains one of humanity’s most enduring mysteries. It’s been the topic of intense psychological research for decades, spawning myriad hypotheses of why we choose whom we choose.

“Mate choice is really complicated, especially in humans,” said Dan Conroy-Beam(link is external), an assistant professor in the Department of Psychological and Brain Sciences at UC Santa Barbara, and author of a paper(link is external) in the journal Personality and Social Psychology Review. “And there have been a lot of people who have proposed abstract ideas about how it might happen.”

One line of thinking, for instance, posits that we assess potential mates against an internal threshold of preferred qualities and attributes — a “minimum bar,” that they have to meet to be considered a potential partner.

“And we learn where that minimum bar is based on how other people treat us,” he said. Another model describes the dating market somewhat like the European social dances of the 18th century.

“One side approaches the other side and they get these kinds of temporary relationships going,” Conroy-Beam said. “And basically you stay in a relationship until you get a better offer and everybody kind of recurrently ditches their partners for better ones.”

But these mate selection models, and others like them, don’t capture a lot of the nuance that goes into real-life mate selection, Conroy-Beam noted.

“When you have a system that is particularly complicated like human mating markets are, verbal models are sometimes not such a great way to understand what’s going on,” he said. Competing desires and social dynamics play heavily into mate selection, he explained, adding layers of complexity and moving parts that can’t be captured or quantified.

So what can hold human-like multiple levels of detail and complexity? The next best thing: a computer simulation. In an effort to move understanding of mate choice forward, Conroy-Beam has developed a new approach — called “couple simulation” — that essentially test-drives models of mate selection against the attributes and priorities of a sample of real-life couples.

“The real advantage that we have here is that we’re going away from just these verbal models and into explicit computational models,” he said. “We’re directly simulating people’s real choices; we’re removing the limits of doing this in our own heads because we have computers that can keep track of all the very complicated interactions that are going on.”

Sim Dating

The process begins by measuring the traits and preferences of a population of a few hundred couples — real people who have made real-life mate choices. That data is crunched into simulated copies of each person — “avatar agents” that have the same attributes and desires as their human counterparts, except in the simulated world they’re single.

“We break them up and throw all these little agents into the market,” said Conroy-Beam, who received support for his research from the National Science Foundation’s Early CAREER program. “Then we run various algorithms and see which ones do the best job at putting them back together with the agent representing their real-world partner.”

The algorithms represent different models of mate selection, which dictate the rules by which the agents can interact, based on the predictions of the model. In addition to the Aspiration Threshold Model (minimum bar) and the Gale-Shapley Algorithm (optimizing stable pairs), the team also used the Kalick-Hamilton Model (KHM), which assumes people choose mates according to their attractiveness, and a new model Conroy-Beam proposed called the Resource Allocation Model (RAM).

“It’s thinking about mate choice in terms of investment of limited resources,” he said. “So you’ve only got so much time and so much money and so much energy that you can dedicate to potential partners. And so your question as the person who’s looking for a partner is ‘who deserves most of these limited resources?'”

Conroy-Beam’s model, it turns out, proved to be the most accurate, correctly matching approximately 45% of the couples in the simulated market in the very first runs of couple simulation. What makes the Resource Allocation Model work so well?

“There are a number of differences between RAM and the other models,” he said. “The other models treat attraction like an on/off switch, but RAM allows for gradients of attraction. It also incorporates reciprocity: the more a potential mate pursues you, the more you pursue them in return,” he said. The Gale-Shapley algorithm came in second, followed by the aspirational threshold model and then the KHM (attractiveness). Random pairings came in last.

It’s still early days for couple simulation; after all, Conroy-Beam said, 45% right is still 55% wrong. For a first pass, however, 45% accuracy is impressive, and according to the study, the people in this cohort also report having higher-quality relationships (more satisfied, more committed, more love, less jealous) than the people in the inaccurately paired couples.

Conroy-Beam and his team at the Computational Mate Choice Lab at UCSB will continue to refine their models, which he calls “really rough sketches,” to increase accuracy. They’re hoping to soon conduct a longer term longitudinal study to see if couples that are accurately predicted differ in longevity.

“We hope to do this across cultures as well as to incorporate same-sex couples in the near future,” he said. “We also have plans in the next couple of years to try to apply this to single people to prospectively predict their future relationships.”

This research was supported by NSF Early CAREER award 1845586

The article was written by NIAID Director Anthony S. Fauci, M.D.; John R. Mascola, M.D., director of NIAID’s Vaccine Research Center (VRC); and Barney S. Graham, M.D., Ph.D., deputy director of NIAID’s VRC.

The authors note that the overlapping discovery of several SARS-CoV-2 variants has led to confusing terms used to name them. The appearance of SARS-CoV-2 variants is so recent that the World Health Organization and other groups are still developing appropriate nomenclature for the different variants.

Numerous SARS-CoV-2 variants have emerged over the last several months. The authors note that the variants known as B.1.1.7 (first identified in the United Kingdom) and B.1.351 (first identified in South Africa) concern scientists because of emerging data suggesting their increased transmissibility.

Variants can carry several different mutations, but changes in the spike protein of the virus, used to enter cells and infect them, are especially concerning. Changes to this protein may cause a vaccine to be less effective against a particular variant. The authors note that the B.1.351 variant may be partially or fully resistant to certain SARS-CoV-2 monoclonal antibodies currently authorized for use as therapeutics in the United States.

The recognition of all new variants, including a novel emergent strain (20C/S:452R) in California, requires systematic evaluation, according to the authors. The rise of these variants is a reminder that as long as SARS-CoV-2 continues to spread, it has the potential to evolve into new variants, the authors stress. Therefore, the fight against SARS-CoV-2 and COVID-19 will require robust surveillance, tracking, and vaccine deployment worldwide.

The authors also note the need for a pan-coronavirus vaccine. Once researchers know more about how the virus changes as it spreads, it may be possible to develop a vaccine that protects against most or all variants. While similar research programs are already in place for other diseases, such as influenza, the changing nature of SARS-CoV-2 indicates that they will be necessary for this virus.

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The investigators examined data from 291 participants who had been followed from toddlerhood to young adulthood as part of a larger study on temperament and socioemotional development. The researchers found that participants who continued to show a temperament characteristic called behavioral inhibition in childhood were more likely to experience worry dysregulation in adolescence (age 15), which in turn predicted elevated anxiety during the early months of the COVID-19 pandemic when the participants were in young adulthood (around age 18).

“People differ greatly in how they handle stress,” said Daniel Pine, M.D., a study author and chief of the National Institute of Mental Health (NIMH) Section on Development and Affective Neuroscience. “This study shows that children’s level of fearfulness predicts how much stress they experience later in life when they confront difficult circumstances, such as the pandemic.”

Behavioral inhibition is a childhood temperament characterized by high levels of cautious, fearful, and avoidant responses to unfamiliar people, objects, and situations. Previous studies have established that children who display behavioral inhibition are at increased risk of developing anxiety disorders later. However, less research has investigated the specific mechanisms by which a stable pattern of behavioral inhibition in childhood is linked to anxiety in young adulthood.

The authors of this study hypothesized that children who demonstrate a stable pattern of behavioral inhibition may be at greater risk for worry dysregulation in adolescence — that is, difficulties managing worry and displaying inappropriate expressions of worry — and this would put them at greater risk for later heightened anxiety during stressful events like the pandemic.

In the larger study, behavioral inhibition was measured at ages 2 and 3 using observations of children’s responses to novel toys and interaction with unfamiliar adults. When the children were 7 years old, they were observed for social wariness during an unstructured free play task with an unfamiliar peer. Worry dysregulation was assessed at age 15 through a self-report survey. For the current study, the participants, at an average age of 18, were assessed for anxiety twice during the early months of the COVID-19 pandemic after stay-at-home orders had been issued (first between April 20 and May 15 and approximately a month later).

At the first assessment, 20% of the participants reported moderate levels of anxiety symptoms considered to be in the clinical range. At the second assessment, 18.3% of participants reported clinical levels of anxiety. As expected, the researchers found that individuals with high behavioral inhibition in toddlerhood who continued to display high levels of social wariness in childhood reported experiencing dysregulated worry in adolescence, and this ultimately predicted increased anxiety in young adulthood during a critical stage of the pandemic. This developmental pathway was not significant for children who showed behavioral inhibition in toddlerhood but displayed low levels of social wariness later in childhood.

“This study provides further evidence of the continuing impact of early life temperament on the mental health of individuals,” said Nathan A. Fox, Ph.D., Distinguished University Professor and director of the Child Development Lab at the University of Maryland, College Park, and an author of the study. “Young children with stable behavioral inhibition are at heightened risk for increased worry and anxiety, and the context of the pandemic only heightened these effects.”

The findings suggest that targeting social wariness in childhood and worry dysregulation in adolescence may be a viable strategy for the prevention of anxiety disorders. The findings also suggest that targeting dysregulated worry in adolescence may be particularly important for identifying those who might be at risk for heightened anxiety during stressful life events like the COVID-19 pandemic and preventing that heightened anxiety.

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Fin whale songs contain signals that are reflected and refracted within the crust, including the sediment and the solid rock layers beneath. These signals, recorded on seismometers on the ocean bottom, can be used to determine the thickness of the layers as well as other information relevant to seismic research, said John Nabelek, a professor in Oregon State University’s College of Earth, Ocean, and Atmospheric Sciences and a co-author of the paper.

“People in the past have used whale calls to track whales and study whale behavior. We thought maybe we can study the Earth using those calls,” Nabelek said. “What we discovered is that whale calls may serve as a complement to traditional passive seismic research methods.”

The paper serves as a proof of concept that could provide new avenues for using data from whale calls in research, Nabelek said.

“This expands the use of data that is already being collected,” he said. “It shows these animal vocalizations are useful not just for understanding the animals, but also understanding their environment.”

The study’s lead author is Vaclav M. Kuna, who worked on the project as a doctoral student at Oregon State and has since completed his Ph.D.

Kuna and Nabelek were studying earthquakes from a network of 54 ocean-bottom seismometers placed along the Blanco transform fault, which at its closest is about 100 miles off Cape Blanco on the Oregon Coast.

They noted strong signals on the seismometers that correlated with whales’ presence in the area.

“After each whale call, if you look closely at the seismometer data, there is a response from the Earth,” Nabelek said.

Whale calls bounce between the ocean surface and the ocean bottom. Part of the energy from the calls transmits through the ground as a seismic wave. The wave travels through the oceanic crust, where it is reflected and refracted by the ocean sediment, the basalt layer underneath it and the gabbroic lower crust below that.

When the waves are recorded at the seismometer, they can provide information that allows researchers to estimate and map the structure of the crust.

Using a series of whale songs that were recorded by three seismometers, the researchers were able to pinpoint the whale’s location and use the vibrations from the songs to create images of the Earth’s crust layers.

Researchers use information from these layers to learn more about the physics of earthquakes in the region, including how sediment behaves and the relationship between its thickness and velocity. Earthquakes shake up the sediment, expelling water and speeding up the settlement of the sediment.

The current traditional method for imaging of the crust can be expensive and permits can be difficult to obtain because the work involves deploying air guns, Nabelek said. The imaging created using the whale songs is less invasive, though overall it is of lower resolution.

Future research could include using machine learning to automate the process of identifying whale songs and developing images of their surroundings, Nabelek said.

“The data from the whale songs is useful but it doesn’t completely replace the standard methods,” he said. “This method is useful for investigating the Earth’s oceanic crust where standard science survey methods are not available.”

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Materials provided by Oregon State University. Original written by Michelle Klampe. Note: Content may be edited for style and length.

Published by the journal Nature, research co-authored by University of Massachusetts Amherst physicist Chen Wang, graduate students Jeffrey Gertler and Shruti Shirol, and postdoctoral researcher Juliang Li takes a step toward building a fault-tolerant quantum computer. They have realized a novel type of QEC where the quantum errors are spontaneously corrected.

Today’s computers are built with transistors representing classical bits (0’s or 1’s). Quantum computing is an exciting new paradigm of computation using quantum bits (qubits) where quantum superposition can be exploited for exponential gains in processing power. Fault-tolerant quantum computing may immensely advance new materials discovery, artificial intelligence, biochemical engineering and many other disciplines.

Since qubits are intrinsically fragile, the most outstanding challenge of building such powerful quantum computers is efficient implementation of quantum error correction. Existing demonstrations of QEC are active, meaning that they require periodically checking for errors and immediately fixing them, which is very demanding in hardware resources and hence hinders the scaling of quantum computers.

In contrast, the researchers’ experiment achieves passive QEC by tailoring the friction (or dissipation) experienced by the qubit. Because friction is commonly considered the nemesis of quantum coherence, this result may appear quite surprising. The trick is that the dissipation has to be designed specifically in a quantum manner. This general strategy has been known in theory for about two decades, but a practical way to obtain such dissipation and put it in use for QEC has been a challenge.

“Although our experiment is still a rather rudimentary demonstration, we have finally fulfilled this counterintuitive theoretical possibility of dissipative QEC,” says Chen. “Looking forward, the implication is that there may be more avenues to protect our qubits from errors and do so less expensively. Therefore, this experiment raises the outlook of potentially building a useful fault-tolerant quantum computer in the mid to long run.”

Chen describes in layman’s terms how strange the quantum world can be. “As in German physicist Erwin Schrödinger’s famous (or infamous) example, a cat packed in a closed box can be dead or alive at the same time. Each logical qubit in our quantum processor is very much like a mini-Schrödinger’s cat. In fact, we quite literally call it a `cat qubit.’ Having lots of such cats can help us solve some of the world’s most difficult problems.

“Unfortunately, it is very difficult to keep a cat staying that way since any gas, light, or anything leaking into box will destroy the magic: The cat will become either dead or just a regular live cat,” explains Chen. “The most straightforward strategy to protect a Schrodinger’s cat is to make the box as tight as possible, but that also makes it harder to use it for computation. What we just demonstrated was akin to painting the inside of the box in a special way and that somehow helps the cat better survive the inevitable harm of the outside world.”

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Unlike on Earth, where terrains are commonly dated using natural radioactivity of rocks, scientists have largely constrained the chronology of Mars by counting impact craters on its surface.

“The idea behind crater dating is not rocket science; the more craters, the older the surface,” says SwRI’s Dr. Simone Marchi, who published a paper about these findings accepted for publication in The Astronomical Journal. “But the devil is in the details. Craters form when asteroids and comets strike the surface. The rate of these cosmic crashes over the eons is uncertain, hampering our ability to convert crater numbers to terrain ages. I took a fresh look at this and built on recent developments in the way we understand the earliest evolution of the solar system.”

Scientists have used radiometric ages of precious lunar rocks brought back by the Apollo missions to calibrate a lunar crater chronology. This lunar chronology is then extrapolated to Mars, and this is where things get tangled with the earliest evolution of the solar system. Our understanding of the time evolution of lunar and Martian impact rates has greatly improved in recent years. The present model improves upon how the critical Moon-to-Mars extrapolations are done.

“For this paper, I looked particularly at the Jezero Crater because that is the landing site for the Mars 2020 Perseverance rover,” Marchi said. “These surfaces could have formed over 3 billion years ago, as much as 500 million years older than previously thought. NASA plans to have Perseverance gather and package surface samples that can be collected by a future mission for return to Earth for radiometric dating. That could provide vital ground-truth data to better calibrate our chronology models.”

Jezero Crater has a diameter of about 30 miles located within the 750-mile-wide Isidis Basin, created by an earlier impact. The latter cut a wide portion of the Borealis Basin’s rim, perhaps the largest and oldest impact basin on Mars. This coincidence of nested craters is of particular interest as samples from these terrains may return information about the timing of these consecutive impacts.

Furthermore, Jezero Crater hosts clay-rich terrains and a fluvial delta, indications that the crater once hosted a lake. This makes the Jezero Crater an ideal place to fulfill the Mars 2020 mission’s science goal of studying a potentially habitable environment that may still preserve signs of past life. As such, understanding the timeline of these surfaces is particularly important.

The new model also provides a revised age for Isidis Basin, now estimated to be 4-4.2 billion years old, providing an upper limit for the formation of Jezero Crater and water activity at this location on Mars.

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