The work, led by UAF Geophysical Institute postdoctoral researcher Alex Witsil, was published recently in the journal Geophysical Research Letters.

Witsil, at the Geophysical Institute’s Wilson Alaska Technical Center, and colleagues created a library of synthetic infrasound explosion signals to train computers in recognizing the source of an infrasound signal. Infrasound is at a frequency too low to be heard by humans and travels farther than high-frequency audible waves.

“We used modeling software to generate 28,000 synthetic infrasound signals, which, though generated in a computer, could hypothetically be recorded by infrasound microphones deployed hundreds of kilometers from a large explosion,” Witsil said.

The artificial signals reflect variations in atmospheric conditions, which can alter an explosion’s signal regionally or globally as the sound waves propagate. Those changes can make it difficult to detect an explosion’s origin and type from a great distance.

Why create artificial sounds of explosions rather than use real-world examples? Because explosions haven’t occurred at every location on the planet and the atmosphere constantly changes, there aren’t enough real-world examples to train generalized machine-learning detection algorithms.

“We decided to use synthetics because we can model a number of different types of atmospheres through which signals can propagate,” Witsil said. “So even though we don’t have access to any explosions that happened in North Carolina, for example, I can use my computer to model North Carolina explosions and build a machine-learning algorithm to detect explosion signals there.”

Today, detection algorithms generally rely on infrasound arrays consisting of multiple microphones close to each other. For example, the international Comprehensive Test Ban Treaty Organization, which monitors nuclear explosions, has infrasound arrays deployed worldwide.

“That’s expensive, it’s hard to maintain, and a lot more things can break,” Witsil said.

Witsil’s method improves detection by making use of hundreds of single-element infrasound microphones already in place around the world. That makes detection more cost-effective.

The machine-learning method broadens the usefulness of single-element infrasound microphones by making them capable of detecting more subtle explosion signals in near real-time. Single-element microphones currently are useful only for retroactively analyzing known and typically high-amplitude signals, as they did with January’s massive eruption of the Tonga volcano.

Witsil’s method could be deployed in an operational setting for national defense or natural hazards mitigation.

This work was funded by the Defense Threat Reduction Agency.

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Materials provided by University of Alaska Fairbanks. Original written by Rod Boyce. Note: Content may be edited for style and length.

“We found that in some children, illness with COVID-19 is associated with reporting persistent symptoms after 3 months,” said Principal Investigator Stephen Freedman, MDCM, MSc, with the Cumming School of Medicine at University of Calgary, and Alberta Health Services. “Our results suggest that appropriate guidance and follow-up are needed, especially for children at high risk for long COVID.”

The study included 1,884 children with COVID-19 who had 90-day follow-up. Long COVID was found in nearly 10 percent of hospitalized children and 5 percent in children discharged from the ED.

“Reported rates of long COVID in adults are substantially higher than what we found in children,” said Co-Principal Investigator Nathan Kuppermann, MD, MPH, from University of California, Davis School of Medicine, Sacramento. “Our findings can inform public health policy decisions regarding COVID-19 mitigation strategies for children and screening approaches for long COVID among those with severe infections.”

The most reported persistent symptoms in children were fatigue or weakness, cough, difficulty breathing or shortness of breath.

“Our finding that children who had multiple COVID-19 symptoms initially were at higher risk for long COVID is consistent with studies in adults,” said Co-Principal Investigator Todd Florin, MD, MSCE, from Ann & Robert H. Lurie Children’s Hospital of Chicago and Northwestern University Feinberg School of Medicine. “Unfortunately, there are no known therapies for long COVID in children and more research is needed in this area. However, if symptoms are significant, treatment targeting the symptoms is most important. Multidisciplinary care is warranted if symptoms are impacting quality of life.”

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Materials provided by University of Calgary. Note: Content may be edited for style and length.

Climate change accelerated by excess CO₂ emissions has been a major concern over the past few years. To deal with this problem, technologies that can not only reduce and remove excess CO₂ emissions but also transform them into value-added chemicals are being developed. One such method is the hydrogenation of CO₂ using renewable hydrogen to produce alternative fuels.

Over the years different strategies have been developed to improve CO₂ hydrogenation in the presence of metallic catalysts. The most promising among them is nonthermal plasma (NTP). It promotes hydrogenation of CO₂ beyond the thermodynamic limit even at low temperatures without deactivating metallic catalysts, which are vulnerable to higher temperatures. Despite the rising popularity of this technique, the interactions between the NTP-activated species and metallic catalysts are still not well understood.

Fortunately, a team of researchers from Tokyo Institute of Technology (Tokyo Tech), Japan, led by Prof. Tomohiro Nozaki, devised a study to overcome this gap in understanding. In their recent breakthrough, published in the Journal of the American Chemical Society, the researchers revealed the reaction dynamics for NTP-assisted CO₂ hydrogenation on the surface of Pd₂Ga/SiO₂ alloy catalysts that lead to the formation of formate. Prof Nozaki explains “Reaction mechanisms like Eley-Rideal or E-R pathway have been proposed to explain efficient CO₂ conversion at lower temperatures and the activation energy for this reaction decreases dramatically. Moreover, NTP produces a copious amount of vibrationally activated CO₂ which is the key to enhancing CO₂ conversion beyond the thermal equilibrium.”

The team investigated the reactions between NTP activated CO₂ and Pd₂Ga/SiO₂ alloy catalysts in a fluidized-bed dielectric barrier discharge reactor  and compared them to conventional thermal catalysis. The results revealed that the CO₂ conversion into formate was more than two-fold in the case of NTP-assisted hydrogenation when compared to thermal conversion. To further establish the mechanics of the mentioned conversion, the scientists adopted in situ spectroscopic analysis and density functional theory (DFT) calculations.

The results revealed that the NTP activation gave rise to vibrationally excited CO₂ molecules which directly react with hydrogen atoms adsorbed by the Pd sites on the catalyst via the E-R pathway. One of the O atoms from the reacted species then got adsorbed at the neighboring Ga site resulting in the formation of monodentate-formate or m-HCOO. The DFT calculations also deduced a decomposition pathway for the same m-HCOO species.

This experimental-theoretical study showed that NTP can promote CO₂ hydrogenation to limits those conventional thermal methods can hardly reach. It also provided mechanistic insights into NTP activated CO₂ and catalyst interaction, which can be utilized to develop better catalysts and improve the hydrogenation process. “With our research, we wanted to accelerate the waste to wealth initiative. Capturing CO₂ and using it as feedstock for synthesis of fuels and valuable chemicals will not only help us deal with climate problem but also slow down fossil fuel depletion to some extent,” concludes Prof. Nozaki.

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Materials provided by Tokyo Institute of Technology. Note: Content may be edited for style and length.