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How hummingbirds hum: New measurement technique unravels what gives hummingbird wings their characteristic sound

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How hummingbirds hum: New measurement technique unravels what gives hummingbird wings their characteristic sound

The hummingbird is named after its pleasant humming sound when it hovers in front of flowers to feed. But only now has it become clear how the wing generates the hummingbird’s namesake sound when it is beating rapidly at 40 beats per second. Researchers from Eindhoven University of Technology, Sorama, a TU/e spin-off company, and Stanford University meticulously observed hummingbirds using 12 high-speed cameras, 6 pressure plates and 2176 microphones. They discovered that the soft and complex feathered wings of hummingbirds generate sound in a fashion similar to how the simpler wings of insect do. The new insights could help make devices like fans and drones quieter.

The team of engineers succeeded in measuring the precise origin of the sound generated by the flapping wings of a flying animal for the first time. The hummingbird’s hum originates from the pressure difference between the topside and underside of the wings, which changes both in magnitude and orientation as the wings flap back and forth. These pressure differences over the wing are essential, because they furnish the net aerodynamic force that enables the hummingbird bird to liftoff and hover.Unlike other species of birds, a hummingbird wing generates a strong upward aerodynamic force during both the downward and upward wing stroke, so twice per wingbeat. Whereas both pressure differences due to the lift and drag force acting on the wing contribute, it turns out that the upward lifting pressure difference is the primary source of the hum.

The difference between whining, humming, buzzing and wooshing

Professor David Lentink of Stanford University: “This is the reason why birds and insects make different sounds. Mosquitoes whine, bees buzz, hummingbirds hum, and larger birds ‘woosh’. Most birds are relatively quiet because they generate most of the lift only once during the wingbeat at the downstroke. Hummingbirds and insects are noisier because they do so twice per wingbeat.”

The researchers combined all measurements in a 3D acoustic model of bird and insect wings. The model not only provides biological insight into how animals generate sound with their flapping wings, it also predicts how the aerodynamic performance of a flapping wing gives the wing sound its volume and timbre. “The distinctive sound of the hummingbird is perceived as pleasant because of the many ‘overtones’ created by the varying aerodynamic forces on the wing. A hummingbird wing is similar to a beautifully tuned instrument,” Lentink explains with a smile.

High-tech sound camera

To arrive at their model, the scientists examined six Anna’s hummingbirds, the most common species around Stanford. One by one, they had the birds drink sugar water from a fake flower in a special flight chamber. Around the chamber, not visible to the bird, cameras, microphones and pressure sensors were set up to precisely record each wingbeat while hovering in front of the flower.You can’t just go out and buy the equipment needed for this from an electronics store. CEO and researcher Rick Scholte of Sorama, a spin-off of TU Eindhoven: “To make the sound visible and be able to examine it in detail, we used sophisticated sound cameras developed by my company. The optical cameras are connected to a network of 2176 microphones for this purpose. Together they work a bit like a thermal camera that allows you to show a thermal image. We make the sound visible in a ‘heat map’, which enables us to see the 3D sound field in detail.”

New aerodynamic force sensors

To interpret the 3D sound images, it is essential to know what motion the bird’s wing is making at each sound measurement point. For that, Stanford’s twelve high-speed cameras came into play, capturing the exact wing movement frame-by-frame.Lentink: “But that’s not end of story. We also needed to measure the aerodynamic forces the hummingbird’s wings generates in flight. We had to develop a new instrument for that.” During a follow-up experiment six highly sensitive pressure plates finally managed to record the lift and drag forces generated by the wings as they moved up and down, a first.

The terabytes of data then had to be synchronized. The researchers wanted to know exactly which wing position produced which sound and how this related to the pressure differences. Scholte: “Because light travels so much faster than sound, we had to calibrate each frame separately for both the cameras and the microphones, so that the sound recordings and the images would always correspond exactly.” Because the cameras, microphones and sensors were all in different locations in the room, the researchers also had to correct for that.

Algorithm as a composite artist

Once the wing location, the corresponding sound and the pressure differences are precisely aligned for each video frame, the researchers were confronted with the complexity of interpretating high volume data. The researchers tackled this challenge harnessing artificial intelligence, the research of TU/e PhD student, and co-first author, Patrick Wijnings.

Wijnings: “We developed an algorithm for this that can interpret a 3D acoustic field from the measurements, and this enabled us to determine the most probable sound field of the hummingbird. The solution to this so-called inverse problem resembles what a police facial composite artist does: using a few clues to make the most reliable drawing of the suspect. In this way, you avoid the possibility that a small distortion in the measurements changes the outcome.”

The researchers finally managed to condense all these results in a simple 3D acoustic model, borrowed from the world of airplanes and mathematically adapted to flapping wings. It predicts the sound that flapping wings radiate, not only the hum of the hummingbird, but also the woosh of other birds and bats, the buzzing and whining of insects and even the noise that robots with flapping wings generate.

Making drones quieter

Although it was not the focus of this study, the knowledge gained may also help improve aircraft and drone rotors as well as laptop and vacuum cleaner fans. The new insights and tools can help make engineered devices that generate complex forces like animals do quieter.

This is exactly what Sorama aims to do: “We make sound visible in order to make appliances quieter. Noise pollution is becoming an ever-greater problem. And a decibel meter alone is not going to solve that. You need to know where the sound comes from and how it is produced, in order to be able to eliminate it. That’s what our sound cameras are for. This hummingbird wing research gives us a completely new and very accurate model as a starting point, so we can do our work even better,” concludes Scholte.

This research appears on March 16 in the journal eLife, under the title “How Oscillating Aerodynamic Forces Explain the Timbre of the Hummingbird’s Hum and Other Animals in Flapping Flight.” The experimental and analytical work of this research was conducted by PhD student Patrick Wijnings of TU Eindhoven under the supervision of Rick Scholte of Sorama and Sander Stuijk and Henk Corporaal of TU/e, and PhD student Ben Hightower of Stanford under the supervision of David Lentink of Stanford University with the assistance of four co-authors from the Lentink Lab: Rivers Ingersoll, Diana Chin, Jade Nguyen and Daniel Shorr. This research was financed by NWO Perspectief program ZERO and CAREER AWARD National Science Foundation (NSF).

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Simple test for flu could improve diagnosis and surveillance

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How hummingbirds hum: New measurement technique unravels what gives hummingbird wings their characteristic sound


Fewer than one percent of people who get the flu every year get tested, in part because most tests require trained personnel and expensive equipment. Now researchers have developed a low-cost paper strip test that could allow more patients to find out which type of flu they have and get the right treatment.

The test, developed by a team from the Broad Institute of MIT and Harvard and Princeton University, and supported by the US Centers for Disease Control and Prevention, uses CRISPR to distinguish between the two main types of seasonal flu, influenza A and B, as well as seasonal flu subtypes H1N1 and H3N2. It can also identify strains that resist antiviral treatment, and with further work, could potentially detect swine and avian flu strains, including H5N1, which is currently infecting cattle.

Appearing in The Journal of Molecular Diagnostics, the results could help improve outbreak response and clinical care by bringing tests that are accurate, low-cost, and fast to doctors’ offices and labs across the US and in other countries.

“Ultimately, we hope these tests will be as simple as rapid antigen tests, and they’ll still have the specificity and performance of a nucleic acid test that would normally be done in a laboratory setting,” said Cameron Myhrvold, co-senior author on the study along with Pardis Sabeti, an institute member at the Broad and a professor at Harvard University and the Harvard T.H. Chan School of Public Health, as well as a Howard Hughes Medical Institute investigator. Myhrvold, who is currently an assistant professor at Princeton University, was a postdoctoral researcher in Sabeti’s lab when the study began.

SHINE a light

The test is based on a technology called SHINE, which was developed by Sabeti’s lab in 2020 and uses CRISPR enzymes to identify specific sequences of viral RNA in samples. The researchers first used SHINE to test for SARS-CoV-2, and later to distinguish between the Delta and Omicron variants. Then, in 2022, they began adapting the assay to detect other viruses they knew were always circulating: influenzas. They wanted to create tests that could be used in the field or in clinics rather than hospitals or diagnostic labs with expensive equipment.

“Using a paper strip readout instead of expensive fluorescence machinery is a big advancement, not only in terms of clinical care but also for epidemiological surveillance purposes,” said Ben Zhang, co-first author on the study, a medical student at Harvard Medical School and an undergraduate researcher in Sabeti’s lab when the study began.

Typical diagnostic approaches such as polymerase chain reaction (PCR) require lengthy processing times, trained personnel, specialized equipment, and freezers to store reagents at -80°C, whereas SHINE can be conducted at room temperature in about 90 minutes. Currently, the assay only requires an inexpensive heat block to warm the reaction, and the researchers are working to streamline the process with the goal of returning results in 15 minutes.

The researchers also adapted SHINE to distinguish between different flu strains. In the future, they say the assay could be adapted to detect two different viruses with similar symptoms, such as influenza and SARS-CoV-2.

“Being able to tease apart what strain or subtype of influenza is infecting a patient has repercussions both for treating them and public health interventions,” said Jon Arizti-Sanz, a postdoctoral researcher in Sabeti’s lab and co-first author on the study.

For example, the tests could help clinicians decide whether to use Oseltamivir, a common antiviral that is effective for only some strains, Arizti-Sanz added. In the field, rapid testing could also help scientists collect samples more strategically during an outbreak to better monitor how the virus is spreading.

Next, the researchers are adapting SHINE to test for both avian and swine influenza strains. “With SARS-CoV-2 and now flu, we’ve shown that we can easily adapt SHINE to detect new or evolving viruses,” Arizti-Sanz said. “We’re excited to apply it to H5N1.”



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Prying open the AI black box

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How hummingbirds hum: New measurement technique unravels what gives hummingbird wings their characteristic sound


Artificial intelligence continues to squirm its way into many aspects of our lives. But what about biology, the study of life itself? AI can sift through hundreds of thousands of genome data points to identify potential new therapeutic targets. While these genomic insights may appear helpful, scientists aren’t sure how today’s AI models come to their conclusions in the first place. Now, a new system named SQUID arrives on the scene armed to pry open AI’s black box of murky internal logic.

SQUID, short for Surrogate Quantitative Interpretability for Deepnets, is a computational tool created by Cold Spring Harbor Laboratory (CSHL) scientists. It’s designed to help interpret how AI models analyze the genome. Compared with other analysis tools, SQUID is more consistent, reduces background noise, and can lead to more accurate predictions about the effects of genetic mutations.

How does it work so much better? The key, CSHL Assistant Professor Peter Koo says, lies in SQUID’s specialized training.

“The tools that people use to try to understand these models have been largely coming from other fields like computer vision or natural language processing. While they can be useful, they’re not optimal for genomics. What we did with SQUID was leverage decades of quantitative genetics knowledge to help us understand what these deep neural networks are learning,” explains Koo.

SQUID works by first generating a library of over 100,000 variant DNA sequences. It then analyzes the library of mutations and their effects using a program called MAVE-NN (Multiplex Assays of Variant Effects Neural Network). This tool allows scientists to perform thousands of virtual experiments simultaneously. In effect, they can “fish out” the algorithms behind a given AI’s most accurate predictions. Their computational “catch” could set the stage for experiments that are more grounded in reality.

“In silico [virtual] experiments are no replacement for actual laboratory experiments. Nevertheless, they can be very informative. They can help scientists form hypotheses for how a particular region of the genome works or how a mutation might have a clinically relevant effect,” explains CSHL Associate Professor Justin Kinney, a co-author of the study.

There are tons of AI models in the sea. More enter the waters each day. Koo, Kinney, and colleagues hope that SQUID will help scientists grab hold of those that best meet their specialized needs.

Though mapped, the human genome remains an incredibly challenging terrain. SQUID could help biologists navigate the field more effectively, bringing them closer to their findings’ true medical implications.



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Iron meteorites hint that our infant solar system was more doughnut than dartboard

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How hummingbirds hum: New measurement technique unravels what gives hummingbird wings their characteristic sound


Four and a half billion years ago, our solar system was a cloud of gas and dust swirling around the sun, until gas began to condense and accrete along with dust to form asteroids and planets. What did this cosmic nursery, known as a protoplanetary disk, look like, and how was it structured? Astronomers can use telescopes to “see” protoplanetary disks far away from our much more mature solar system, but it is impossible to observe what ours might have looked like in its infancy — only an alien billions of light years away would be able to see it as it once was.

Fortunately, space has dropped a few clues — fragments of objects that formed early in solar system history and plunged through Earth’s atmosphere, called meteorites. The composition of meteorites tells stories of the solar system’s birth, but these stories often raise more questions than answers.

In a paper published in Proceedings of the National Academy of Sciences, a team of planetary scientists from UCLA and Johns Hopkins University Applied Physics Laboratory reports that refractory metals, which condense at high temperatures, such as iridium and platinum, were more abundant in meteorites formed in the outer disk, which was cold and far away from the sun. These metals should have formed close to the sun, where the temperature was much higher. Was there a pathway that moved these metals from the inner disk to the outer?

Most meteorites formed within the first few million years of solar system history. Some meteorites, called chondrites, are unmelted conglomerations of grains and dust left over from planet formation. Other meteorites experienced enough heat to melt while their parent asteroids were forming. When these asteroids melted, the silicate part and the metallic part separated due to their difference in density, similar to how water and oil don’t mix.

Today, most asteroids are located in a thick belt between Mars and Jupiter. Scientists think that Jupiter’s gravity disrupted the course of these asteroids, causing many of them to smash into each other and break apart. When pieces of these asteroids fall to Earth and are recovered, they are called meteorites.

Iron meteorites are from the metallic cores of the earliest asteroids, older than any other rocks or celestial objects in our solar system. The irons contain molybdenum isotopes that point toward many different locations across the protoplanetary disk in which these meteorites formed. That allows scientists to learn what the chemical composition of the disk was like in its infancy.

Previous research using the Atacama Large Millimeter/submillimeter Array in Chile has found many disks around other stars that resemble concentric rings, like a dartboard. The rings of these planetary disks, such as HL Tau, are separated by physical gaps, so this kind of disk could not provide a route to transport these refractory metals from the inner disk to the outer.

The new paper holds that our solar disk likely didn’t have a ring structure at the very beginning. Instead, our planetary disk looked more like a doughnut, and asteroids with metal grains rich in iridium and platinum metals migrated to the outer disk as it rapidly expanded.

But that confronted the researchers with another puzzle. After the disk expansion, gravity should have pulled these metals back into the sun. But that did not happen.

“Once Jupiter formed, it very likely opened a physical gap that trapped the iridium and platinum metals in the outer disk and prevented them from falling into the sun,” said first author Bidong Zhang, a UCLA planetary scientist. “These metals were later incorporated into asteroids that formed in the outer disk. This explains why meteorites formed in the outer disk — carbonaceous chondrites and carbonaceous-type iron meteorites — have much higher iridium and platinum contents than their inner-disk peers.”

Zhang and his collaborators previously used iron meteorites to reconstruct how water was distributed in the protoplanetary disk.

“Iron meteorites are hidden gems. The more we learn about iron meteorites, the more they unravel the mystery of our solar system’s birth,” Zhang said.



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