Amazing Science

One of the great puzzles of modern space science is neatly summed up by the view from NASA’s Perseverance, which just landed on Mars: Today it’s a desert planet, and yet the rover is sitting right next to an ancient river delta. The apparent contradiction has puzzled scientists for decades, especially because at the same time that Mars had flowing rivers, it was getting less than a third as much sunshine as we enjoy today on Earth.

But a new study led by University of Chicago planetary scientist Edwin Kite, an assistant professor of geophysical sciences and an expert on climates of other worlds, uses a computer model to put forth a promising explanation: Mars could have had a thin layer of icy, high-altitude clouds that caused a greenhouse effect.

“There’s been an embarrassing disconnect between our evidence, and our ability to explain it in terms of physics and chemistry,” said Kite. “This hypothesis goes a long way toward closing that gap.”

Of the multiple explanations scientists had previously put forward, none have ever quite worked. For example, some suggested that a collision from a huge asteroid could have released enough kinetic energy to warm the planet. But other calculations showed this effect would only last for a year or two—and the tracks of ancient rivers and lakes show that the warming likely persisted for at least hundreds of years.

Kite and his colleagues wanted to revisit an alternate explanation: High-altitude clouds, like cirrus on Earth. Even a small amount of clouds in the atmosphere can significantly raise a planet’s temperature, a greenhouse effect similar to carbon dioxide in the atmosphere.

For the past 150 years or so, scientists have theorized that the life cycle of the present-day lamprey mirrors the evolution of all fish – and thus of all vertebrates. Newly analyzed fossils, however, indicate that such is not the case.

The lamprey is a long eel-like fish, which latches onto the bodies of other fish using its sucker-like mouth. A ring of teeth within that mouth then rasps away the skin of the host fish, so the lamprey can feed on its blood. And while adult lampreys are free-swimming, sighted fish, their larvae are tiny blind worm-like creatures that burrow into the riverbed, then filter-feed on food particles carried past in the current.

Because previously discovered fossils indicated that adult lampreys have changed very little over the past 360 million years (or more), it was thought that their life cycle was just as ancient. Scientists thus theorized that the animals' transition from bottom-dwelling filter-feeders to free-swimming predators was a remnant of the process in which wormy invertebrates eventually evolved into the first vertebrate fishes.

Now, though, fossils of lamprey hatchlings discovered in Illinois, South Africa and Montana are challenging that theory. Some of the fossilized remains include an egg sac, indicating that the creatures had only recently hatched. And importantly, they looked very much like miniature adult lampreys, complete with eyes and tooth-lined sucker mouths. In other words, they were not similar to today's riverbed-burrowing larvae.

Based on these findings, it is now thought that the filter-feeding larval stage may have subsequently evolved as a means of adapting to life in freshwater lakes and rivers – originally, lampreys were strictly marine animals.

Single-photon imaging is the future of high-speed digital photography and vastly surpasses conventional cameras in low-light conditions. However, fixing the blurring caused by the motion of independent objects remains challenging. Recently, researchers at Tokyo University of Science developed an innovative deblurring approach that accurately estimates the motion of individual objects and adjusts the final image accordingly. Their strategy produces high-quality images even in complex dynamic scenes and may find applications in medicine, science, and security.

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America’s new normal temperature is a degree hotter than it was just two decades ago. Scientists have long talked about climate change — hotter temperatures, changes in rain and snowfall and more extreme weather — being the “new normal.” Data released Tuesday by the National Oceanic and Atmospheric Administration put hard figures on the cliche.

The new United States normal is not just hotter, but wetter in the eastern and central parts of the nation and considerably drier in the West than just a decade earlier.

Meteorologists calculate climate normals based on 30 years of data to limit the random swings of daily weather. It’s a standard set by the World Meteorological Organization. Every 10 years, NOAA updates normal for the country as a whole, states and cities — by year, month and season.

Collaboration between deep learning experts and microscopy experts leads to a significantly improved data-intensive light-field microscopy method by using AI and pairing it with light-sheet microscopy. The result is the power of light-field microscopy available to biologists in near real time vs. days or weeks, AND the expansion of biologists' ability to use this microscopy for many things more things requiring the most detailed observation.

To observe the swift neuronal signals in a fish brain, scientists have started to use a technique called light-field microscopy, which makes it possible to image such fast biological processes in 3D. But the images are often lacking in quality, and it takes hours or days for massive amounts of data to be converted into 3D volumes and movies.

Now, EMBL scientists have combined artificial intelligence (AI) algorithms with two cutting-edge microscopy techniques - an advance that shortens the time for image processing from days to mere seconds, while ensuring that the resulting images are crisp and accurate. The findings are published in Nature Methods.

"Ultimately, we were able to take 'the best of both worlds' in this approach," says Nils Wagner, one of the paper's two lead authors and now a PhD student at the Technical University of Munich. "AI enabled us to combine different microscopy techniques, so that we could image as fast as light-field microscopy allows and get close to the image resolution of light-sheet microscopy."

Although light-sheet microscopy and light-field microscopy sound similar, these techniques have different advantages and challenges. Light-field microscopy captures large 3D images that allow researchers to track and measure remarkably fine movements, such as a fish larva's beating heart, at very high speeds. But this technique produces massive amounts of data, which can take days to process, and the final images usually lack resolution.

Light-sheet microscopy homes in on a single 2D plane of a given sample at one time, so researchers can image samples at higher resolution. Compared with light-field microscopy, light-sheet microscopy produces images that are quicker to process, but the data are not as comprehensive, since they only capture information from a single 2D plane at a time. To take advantage of the benefits of each technique, EMBL researchers developed an approach that uses light-field microscopy to image large 3D samples and light-sheet microscopy to train the AI algorithms, which then create an accurate 3D picture of the sample.

"If you build algorithms that produce an image, you need to check that these algorithms are constructing the right image," explains Anna Kreshuk, the EMBL group leader whose team brought machine learning expertise to the project. In the new study, the researchers used light-sheet microscopy to make sure the AI algorithms were working, Anna says. "This makes our research stand out from what has been done in the past."

Robert Prevedel, the EMBL group leader whose group contributed the novel hybrid microscopy platform, notes that the real bottleneck in building better microscopes often isn't optics technology, but computation. That's why, back in 2018, he and Anna decided to join forces. "Our method will be really key for people who want to study how brains compute. Our method can image an entire brain of a fish larva, in real time," Robert says.

Three brown dwarfs whirl on their axes at a dizzying rate that might be close to the celestial speed limit for these bodies.

Astronomers have caught three brown dwarfs spinning at the fastest rates ever recorded for these objects, which are sometimes described as ‘failed stars’. Brown dwarfs are celestial objects with masses that fall between those of large, Jupiter-like planets and the smallest ordinary stars. They are cooler and dimmer than ordinary stars because they are too small to sustain long-term nuclear fusion.

Megan Tannock at the University of Western Ontario in London, Canada, and her collaborators analysed nearly 80 brown dwarfs with regular variations in their brightness and light spectrum. Such variations are produced when brighter spots on the stars’ surfaces come in and out of view as the stars rotate. Measuring the period of such variations gives an accurate estimate of how fast a star is spinning.

The authors found that 3 of the brown dwarfs had record-short rotation periods, ranging from 1 hour and 5 minutes to 1 hour and 14 minutes. The similarity between the periods suggests that the objects might be moving at close to a maximum speed limit, beyond which they would break apart.

Rudimentary cross-catalytic replication can be established by double-hairpins of tRNA-like sequences, implying that replication and translation could have emerged along a common evolutionary trajectory.

Can replication and translation emerge in a single mechanism via self-assembly? The key molecule, transfer RNA (tRNA), is one of the most ancient molecules and contains the genetic code. Our experiments show how a pool of oligonucleotides, adapted with minor mutations from tRNA, spontaneously formed molecular assemblies and replicated information autonomously using only reversible hybridization under thermal oscillations. The pool of cross-complementary hairpins self-selected by agglomeration and sedimentation. The metastable DNA hairpins bound to a template and then interconnected by hybridization.

Thermal oscillations separated replicates from their templates and drove an exponential, cross-catalytic replication. The molecular assembly could encode and replicate binary sequences with a replication fidelity corresponding to 85–90 % per nucleotide. The replication by a self-assembly of tRNA-like sequences suggests that early forms of tRNA could have been involved in molecular replication. This would link the evolution of translation to a mechanism of molecular replication.

In September 2020, a team led by astronomers in the United Kingdom announced that they had detected the chemical phosphine in the thick clouds of Venus. The team’s reported detection, based on observations by two Earth-based radio telescopes, surprised many Venus experts. Earth’s atmosphere contains small amounts of phosphine, which may be produced by life. Phosphine on Venus generated buzz that the planet, often succinctly touted as a “hellscape,” could somehow harbor life within its acidic clouds.

Since that initial claim, other science teams have cast doubt on the reliability of the phosphine detection. Now, a team led by researchers at the University of Washington has used a robust model of the conditions within the atmosphere of Venus to revisit and comprehensively reinterpret the radio telescope observations underlying the initial phosphine claim. As they report in a recent paper accepted to the Astrophysical Journal, the U.K.-led group likely wasn’t detecting phosphine at all.

“Instead of phosphine in the clouds of Venus, the data are consistent with an alternative hypothesis: They were detecting sulfur dioxide,” said co-author Victoria Meadows, a UW professor of astronomy. “Sulfur dioxide is the third-most-common chemical compound in Venus’ atmosphere, and it is not considered a sign of life.”

The team behind the new study also includes scientists at NASA’s Caltech-based Jet Propulsion Laboratory, the NASA Goddard Space Flight Center, the Georgia Institute of Technology, the NASA Ames Research Center and the University of California, Riverside.

The UW-led team shows that sulfur dioxide, at levels plausible for Venus, can not only explain the observations but is also more consistent with what astronomers know of the planet’s atmosphere and its punishing chemical environment, which includes clouds of sulfuric acid. In addition, the researchers show that the initial signal originated not in the planet’s cloud layer, but far above it, in an upper layer of Venus’ atmosphere where phosphine molecules would be destroyed within seconds. This lends more support to the hypothesis that sulfur dioxide produced the signal.

We can learn a lot from nature if we listen to it more—and scientists around the world are trying to do just that. From mountain peaks to ocean depths, biologists are increasingly planting audio recorders to unobtrusively eavesdrop on the groans, shrieks, whistles and songs of whales, elephants, bats and especially birds. This summer, for example, more than 2,000 electronic ears will record the soundscape of California’s Sierra Nevada mountain range, generating nearly a million hours of audio. To avoid spending multiple human lifetimes decoding it, researchers are relying on artificial intelligence.

Such recordings can create valuable snapshots of animal communities and help conservationists understand, in vivid detail, how policies and management practices affect an entire population. Gleaning data about the number of species and individuals in a region is just the beginning. The Sierra Nevada soundscape contains crucial information about how last year’s historic wildfires affected birds living in different habitats and ecological conditions across the area. The recordings could reveal how various animal populations weathered the catastrophe and which conservation measures help species rebound more effectively.

Such recordings can also capture details about interactions between individuals in larger groups. For example, how do mates find each other amid a cacophony of consorts? Scientists can additionally use sound to track shifts in migration timing or population ranges. Massive amounts of audio data are pouring in from research elsewhere as well: sound-based projects are underway to count insects, study the effects of light and noise pollution on avian communities, track endangered species, and trigger alerts when recorders detect noise from illegal poaching or logging activities.

“Audio data is a real treasure trove because it contains vast amounts of information,” says ecologist Connor Wood, a Cornell University postdoctoral researcher, who is leading the Sierra Nevada project. “We just need to think creatively about how to share and access [that information].” This is a looming problem because it takes humans a long time to extract useful insights from recordings. Fortunately the latest generation of machine-learning AI systems—which can identify animal species from their calls—can crunch thousands of hours of data in less than a day.

“AI and machine learning has been the big game changer for us,” says Laurel Symes, assistant director of the Cornell Lab of Ornithology’s Center for Conservation Bioacoustics. She studies acoustic communication in animals, including crickets, frogs, bats and birds, and has amassed many months of recordings of katydids (famously vocal long-horned grasshoppers that are an essential part of the food web) in the rain forests of central Panama. Patterns of breeding activity and seasonal population variation are hidden in this audio, but analyzing it is enormously time-consuming: it took Symes and three of her colleagues 600 hours of work to classify various katydid species from just 10 recorded hours of sound. But a machine-learning algorithm her team is developing, called KatydID, performed the same task while its human creators “went out for a beer,” Symes says.

They may be tiny weapons, but Brigham Young University's holography research group has figured out how to create lightsabers -- green for Yoda and red for Darth Vader, naturally -- with actual luminous beams rising from them.

Inspired by the displays of science fiction, the researchers have also engineered battles between equally small versions of the Starship Enterprise and a Klingon Battle Cruiser that incorporate photon torpedoes launching and striking the enemy vessel that you can see with the naked eye.

"What you're seeing in the scenes we create is real; there is nothing computer generated about them," said lead researcher Dan Smalley, a professor of electrical engineering at BYU. "This is not like the movies, where the lightsabers or the photon torpedoes never really existed in physical space. These are real, and if you look at them from any angle, you will see them existing in that space."

It's the latest work from Smalley and his team of researchers who garnered national and international attention three years ago when they figured out how to draw screenless, free-floating objects in space. Called optical trap displays, they're created by trapping a single particle in the air with a laser beam and then moving that particle around, leaving behind a laser-illuminated path that floats in midair; like a "a 3D printer for light."

The research group's new project, funded by a National Science Foundation CAREER grant, goes to the next level and produces simple animations in thin air. The development paves the way for an immersive experience where people can interact with holographic-like virtual objects that co-exist in their immediate space.

"Most 3D displays require you to look at a screen, but our technology allows us to create images floating in space -- and they're physical; not some mirage," Smalley said. "This technology can make it possible to create vibrant animated content that orbits around or crawls on or explodes out of every day physical objects."

To demonstrate that principle, the team has created virtual stick figures that walk in thin air. They were able to demonstrate the interaction between their virtual images and humans by having a student place a finger in the middle of the volumetric display and then film the same stick finger walking along and jumping off that finger.

Smalley and Rogers detail these and other recent breakthroughs in a new paper published in Nature Scientific Reports this month. The work overcomes a limiting factor to optical trap displays: wherein this technology lacks the ability to show virtual images, Smalley and Rogers show it is possible to simulate virtual images by employing a time-varying perspective projection backdrop.

Scientists at the Institute for Basic Science have recently achieved  the highest laser intensity in history. The record-breaking laser intensity over 10^23 W/cm^2 enable scientists to explore novel physical phenomena occurring under extreme physical conditions.

Recently, laser scientists at the Center for Relativistic Laser Science (CoReLS) within the Institute for Basic Science (IBS) in South Korea realized the unprecedented laser intensity of 10^23 W/cm^2. This has been a milestone that has been pursued for almost two decades by many laser institutes around the world.

An ultrahigh intensity laser is an important research tool in several fields of science, including those which explore novel physical phenomena occurring under extreme physical conditions. Since the demonstration of the10^22 W/cm^2 intensity laser by a team at the University of Michigan in 2004, the realization of laser intensity over10^23 W/cm^2 has been pursued for nearly 20 years.

In general, achieving such a level of ultra-high laser intensity requires two things: laser with extremely high power output, and focusing that laser to the smallest spot as possible. While continuous-wave lasers are limited to megawatt-scale intensity, far higher peak power output (on the order of petawatt) is possible in pulsed laser systems by delivering the energy in the time scale as short as femtoseconds. In order to reach the goal of developing the world's most powerful laser, several ultrahigh power laser facilities with outputs of 10 PW and beyond, such as ELI (EU), Apollon (France), EP-OPAL (USA), and SEL (China), have been built or are being planned. A recent study from Osaka University even proposed a concept prototype for an exawatt class laser. Meanwhile, the CoReLS laser team has been operating a 4-PW laser system since 2016. This year in April 2021, they have finally achieved the record-breaking milestone of10^23 W/cm^2 by tightly focusing the multi-PW laser beam.

Several special techniques have been employed to achieve this feat. The power intensity was maximized by using a focusing optics called an off-axis parabolic mirror, which was used to focus a 28 cm laser beam down to a spot only 1.1 micrometers wide. Such a diffraction-limited tight focusing can be obtained only with a clean laser beam without wavefront distortion. The CoReLS laser team, thus, made its PW laser beam as clean as possible using a set of deformable mirrors to correct the wavefront distortion of the PW laser. The CoReLS 4-PW laser is a femtosecond, ultrahigh power Ti:sapphire laser, based on the chirped pulse amplification (CPA) technique. 

Wherever scientists look, they can spot them: whether in remote mountain lakes, in Arctic sea ice, in the deep-ocean floor or in air samples, even in edible fish—thousands upon thousands of microscopic plastic particles in the micro to millimeter range. This microplastic is now even considered one of the defining features of the Anthropocene, the age of the Earth shaped by modern humans.

Microplastics are formed by weathering and physicochemical or biological degradation processes from macroscopic plastic products, such as the tons of plastic waste in the oceans. It is unlikely that these degradation processes will stop at the micrometer scale. And so there is growing concern about the potential harmful effects nanoplastics could have on various ecosystems.

"Numerous media reports suggest, through their sometimes highly emotional coverage, that we are facing a huge problem here," says Empa researcher Bernd Nowack, who has long studied the material flows of synthetic micro- and nanoparticles, for example from textiles or tire abrasion, into the environment. But Nowack says at present this statement can hardly be substantiated by scientific findings: "We don't even know how much nanoplastics there is in the different ecosystems."

Huge gaps in knowledge

This is primarily because it is enormously difficult in terms of measurement technology to identify artificial nanoparticles made of plastic in environmental samples with thousands and thousands of (natural) particles of similar size. Appropriate analytical methods would first have to be developed, says Denise Mitrano of ETH Zurich. And then it would be a matter of understanding exactly what risk the tiny plastic particles—some of which differ considerably in their chemical composition—pose to humans and the environment, in other words: how dangerous they ultimately are. Adds Nowack, "So we can't justifiably say we have a serious problem here—but we also can't say we don't."

That's because the smaller particles become, the more likely they are to reach organs and tissues that are inaccessible to larger particles. The blood-brain barrier or placenta, for instance, prevents particles and macromolecules from passing through until they reach a certain size—or rather, smallness—thereby protecting the tissues and organs "behind" them, i.e. the brain and fetus, respectively, from potentially dangerous substances such as viruses and bacteria. "Even if we ingest microplastics, for example through our food, they probably do not enter our bloodstream or our brain, but are simply excreted again," says Peter Wick, head of Empa's Particles-Biology Interactions lab, who studies the interactions of nanoparticles with biological systems. "With nanoplastics, we can't be so sure."