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In 2016, the U.S. Environmental Protection Agency (EPA) classified ethylene oxide as carcinogenic to humans, particularly when it is inhaled. Despite significant concern over chronic ethylene oxide exposure for people living between Baton Rouge and New Orleans, there are no published reports of ambient concentrations of the carcinogen that aren’t derived from industry self-reported emissions data. So, Peter DeCarlo and colleagues proposed measuring the levels of this gas using optical instruments that quickly measure airborne chemicals and provide results in real time.

They used a mobile monitoring system with equipment mounted on a small truck or van. These mobile laboratories drove a fixed route along a heavily industrialized portion of the corridor.

• One small truck carried a tunable infrared laser direction absorption spectrometer, which measured ambient ethylene oxide in the surrounding air.
• The van carried a cavity ringdown spectrometer to detect downwind of petrochemical sites contaminant plumes, i.e., mixtures of ethylene oxide and other chemicals, which indicate the type of facility that emitted them.

DeCarlo and the team completed 23 130-mile laps with their mobile monitoring vans from January to February 2023. All of the ethylene oxide measurements were higher than EPA estimates, which were gleaned from industry-reported emissions. Specifically, the researchers’ ambient air measurements revealed that most of the region had ethylene oxide levels that correspond to risk levels above EPA’s acceptable upper limit. A few locations had contaminant concentrations that represent potentially serious health risks for facility workers. And the team’s second van, with the cavity ringdown spectrometer, identified chemical plumes up to 7 miles from their likely sources, which are beyond the 6-mile distance of “fenceline communities.” EPA defines fenceline communities as those where people live close enough to highly polluting facilities that they could be directly affected by the emissions of operation.

The researchers hope that this demonstration of a mobile monitoring system helps increase accurate measurements of hazardous air pollution in an area densely populated with ethylene oxide emitters. Their work also highlights important issues related to current detection and reporting methods and associated health impacts on people living near potential pollution sources.

The authors acknowledge funding from Bloomberg Philanthropies and the National Institute of Environmental Health Sciences.

Some coauthors are employed at Aerodyne Research, Inc., which provided a mobile laboratory and field sampling equipment. Some coauthors are employed at Picarro, Inc. which manufactures one of the instruments used in the study.

The findings are detailed in a paper published on June 12 in Science Advances.

The microrobots are an ingenious combination of biology and nanotechnology. They are a joint effort between the labs of Joseph Wang and Liangfang Zhang, both professors in the Aiiso Yufeng Li Family Department of Chemical and Nano Engineering at the UC San Diego Jacobs School of Engineering.

To create the microrobots, researchers chemically attached drug-filled nanoparticles to the surface of green algae cells. The algae, which provide the microrobots with their movement, enable the nanoparticles to efficiently swim around in the lungs and deliver their therapeutic payload to tumors.

The nanoparticles are made of tiny biodegradable polymer spheres, which are loaded with the chemotherapeutic drug doxorubicin and coated with red blood cell membranes. This coating serves a critical function: it protects the nanoparticles from the immune system, allowing them to stay in the lungs long enough to exert their anti-tumor effects. “It acts as a camouflage,” said study co-first author Zhengxing Li, who is a nanoengineering Ph.D. student in both Wang and Zhang’s research groups. “This coating makes the nanoparticle look like a red blood cell from the body, so it will not trigger an immune response.”

This formulation of nanoparticle-carrying algae is safe, the researchers noted. The materials used to make the nanoparticles are biocompatible while the green algae employed, Chlamydomonas reinhardtii, are recognized as safe for use by the U.S. Food and Drug Administration.

This study builds on prior work by Wang and Zhang’s teams using similar microrobots to treat deadly pneumonia in mice. “Those were the first microrobots to be safely tested in the lungs of live animals,” said Wang.

In previous work, the microrobots fought the spread of pneumonia-causing bacteria using a different drug and cell membrane combination for the nanoparticles. By tweaking these components, the team has now tailored the microrobots to fight the spread of cancer cells in the lungs. “We demonstrate that this is a platform technology that can actively and efficiently deliver therapeutics throughout the entire lung tissue to combat different types of deadly diseases in the lungs,” said Zhang.

In the current study, mice with melanoma that had metastasized to the lungs were treated with the microrobots, which were administered to the lungs through a small tube inserted into the windpipe. Treated mice experienced a median survival time of 37 days, an improvement over the 27-day median survival time observed in untreated mice, as well as mice that received either the drug alone or drug-filled nanoparticles without algae.

“The active swimming motion of the microrobots significantly improved distribution of the drug to the deep lung tissue, while prolonging retention time,” said Li. “This enhanced distribution and prolonged retention time allowed us to reduce the required drug dosage, potentially reducing side effects while maintaining high survival efficacy.”

Moving forward, the team is working on advancing this microrobot treatment to trials in larger animals, with the ultimate goal of human clinical trials.

Paper: “Biohybrid microrobots locally and actively deliver drug-loaded nanoparticles to inhibit the progression of lung metastasis.” Co-authors of the study include Fangyu Zhang*, Zhongyuan Guo*, Zhengxing Li*, Hao Luan, Yiyan Yu, Audrey T. Zhu, Shichao Ding, Weiwei Gao and Ronnie H. Fang.

*These authors contributed equally to this work.

This work was supported by the Defense Threat Reduction Agency Joint Science and Technology Office for Chemical and Biological Defense (HDTRA1-21-1-0010) and the National Institutes of Health (R21AI175904).

Michael Troxel, an associate professor of physics at Duke University in Durham, North Carolina, led the simulation campaign as part of a broader project called OpenUniverse. The team is now releasing a 10-terabyte subset of this data, with the remaining 390 terabytes to follow this fall once they’ve been processed.

“Using Argonne’s now-retired Theta machine, we accomplished in about nine days what would have taken around 300 years on your laptop,” said Katrin Heitmann, a cosmologist and deputy director of Argonne’s High Energy Physics division who managed the project’s supercomputer time. “The results will shape Roman and Rubin’s future attempts to illuminate dark matter and dark energy while offering other scientists a preview of the types of things they’ll be able to explore using data from the telescopes.”

A Cosmic Dress Rehearsal

For the first time, this simulation factored in the telescopes’ instrument performance, making it the most accurate preview yet of the cosmos as Roman and Rubin will see it once they start observing. Rubin will begin operations in 2025, and NASA’s Roman will launch by May 2027.

The simulation’s precision is important because scientists will comb through the observatories’ future data in search of tiny features that will help them unravel the biggest mysteries in cosmology.

Roman and Rubin will both explore dark energy — the mysterious force thought to be accelerating the universe’s expansion. Since it plays a major role in governing the cosmos, scientists are eager to learn more about it. Simulations like OpenUniverse help them understand signatures that each instrument imprints on the images and iron out data processing methods now so they can decipher future data correctly. Then scientists will be able to make big discoveries even from weak signals.

“OpenUniverse lets us calibrate our expectations of what we can discover with these telescopes,” said Jim Chiang, a staff scientist at DOE’s SLAC National Accelerator Laboratory in Menlo Park, California, who helped create the simulations. “It gives us a chance to exercise our processing pipelines, better understand our analysis codes, and accurately interpret the results so we can prepare to use the real data right away once it starts coming in.”

Then they’ll continue using simulations to explore the physics and instrument effects that could reproduce what the observatories see in the universe.

Telescopic Teamwork

It took a large and talented team from several organizations to conduct such an immense simulation.

“Few people in the world are skilled enough to run these simulations,” said Alina Kiessling, a research scientist at NASA’s Jet Propulsion Laboratory (JPL) in Southern California and the principal investigator of OpenUniverse. “This massive undertaking was only possible thanks to the collaboration between the DOE, Argonne, SLAC, and NASA, which pulled all the right resources and experts together.”

And the project will ramp up further once Roman and Rubin begin observing the universe.

“We’ll use the observations to make our simulations even more accurate,” Kiessling said. “This will give us greater insight into the evolution of the universe over time and help us better understand the cosmology that ultimately shaped the universe.”

The Roman and Rubin simulations cover the same patch of the sky, totaling about 0.08 square degrees (roughly equivalent to a third of the area of sky covered by a full Moon). The full simulation to be released later this year will span 70 square degrees, about the sky area covered by 350 full Moons.

Overlapping them lets scientists learn how to use the best aspects of each telescope — Rubin’s broader view and Roman’s sharper, deeper vision. The combination will yield better constraints than researchers could glean from either observatory alone.

“Connecting the simulations like we’ve done lets us make comparisons and see how Roman’s space-based survey will help improve data from Rubin’s ground-based one,” Heitmann said. “We can explore ways to tease out multiple objects that blend together in Rubin’s images and apply those corrections over its broader coverage.”

Scientists can consider modifying each telescope’s observing plans or data processing pipelines to benefit the combined use of both.

“We made phenomenal strides in simplifying these pipelines and making them usable,” Kiessling said. A partnership with Caltech/IPAC’s IRSA (Infrared Science Archive) makes simulated data accessible now so when researchers access real data in the future, they’ll already be accustomed to the tools. “Now we want people to start working with the simulations to see what improvements we can make and prepare to use the future data as effectively as possible.”

“This work proposes and demonstrates a new machine-learning framework that bridges the gap between simulation and reality to autonomously control wearable robots to improve mobility and health of humans,” says Hao Su, corresponding author of a paper on the work which will be published June 12 in the journal Nature.

“Exoskeletons have enormous potential to improve human locomotive performance,” says Su, who is an associate professor of mechanical and aerospace engineering at North Carolina State University. “However, their development and broad dissemination are limited by the requirement for lengthy human tests and handcrafted control laws.

“The key idea here is that the embodied AI in a portable exoskeleton is learning how to help people walk, run or climb in a computer simulation, without requiring any experiments,” says Su.

Specifically, the researchers focused on improving autonomous control of embodied AI systems — which are systems where an AI program is integrated into a physical robot technology. This work focused on teaching robotic exoskeletons how to assist able-bodied people with various movements. Normally, users have to spend hours “training” an exoskeleton so that the technology knows how much force is needed — and when to apply that force — to help users walk, run or climb stairs. The new method allows users to utilize the exoskeletons immediately.

“This work is essentially making science fiction reality — allowing people to burn less energy while conducting a variety of tasks,” says Su.

“We have developed a way to train and control wearable robots to directly benefit humans,” says Shuzhen Luo, first author of the paper and a former postdoctoral researcher at NC State. Luo is now an assistant professor at Embry-Riddle Aeronautical University.

For example, in testing with human subjects, the researchers found that study participants used 24.3% less metabolic energy when walking in the robotic exoskeleton than without the exoskeleton. Participants used 13.1% less energy when running in the exoskeleton, and 15.4% less energy when climbing stairs.

“It’s important to note that these energy reductions are comparing the performance of the robotic exoskeleton to that of a user who is not wearing an exoskeleton,” Su says. “That means it’s a true measure of how much energy the exoskeleton saves.”

While this study focused on the researchers’ work with able-bodied people, the new method also applies to robotic exoskeleton applications aimed at helping people with mobility impairments.

“Our framework may offer a generalizable and scalable strategy for the rapid development and widespread adoption of a variety of assistive robots for both able-bodied and mobility-impaired individuals,” Su says.

“We are in the early stages of testing the new method’s performance in robotic exoskeletons being used by older adults and people with neurological conditions, such as cerebral palsy. And we are also interested in exploring how the method could improve the performance of robotic prosthetic devices for amputee populations.”

This research was done with support from the National Science Foundation under awards 1944655 and 2026622; the National Institute on Disability, Independent Living, and Rehabilitation Research, under award 90DPGE0019 and Switzer Research Fellowship SFGE22000372; and the National Institutes of Health, under award 1R01EB035404.

Shuzhen Luo and Hao Su are co-inventors on intellectual property related to the controller discussed in this work. Su is also a co-founder of, and has a financial interest in, Picasso Intelligence, LLC, which develops exoskeletons.

The findings suggest that the gender of an AI’s voice can positively tweak the dynamics of gender-imbalanced teams and could help inform the design of bots used for human-AI teamwork, researchers said.

The findings mirror previous research that shows minority teammates are more likely to participate if the team adds members similar to them, said Angel Hsing-Chi Hwang, postdoctoral associate in information science and lead author of the paper.

To better understand how AI can help gender-imbalanced teams, Hwang and Andrea Stevenson Won, associate professor of communication and the paper’s co-author, carried out an experiment with around 180 men and women who were assigned to groups of three and asked to collaborate virtually on a set of tasks (the study only included participants who identified as either male or female).

Each group had either one woman or one man and a fourth agent in the form of an abstract shape with either a male or female voice, which would appear on screen and read instructions, contribute an idea and handle timekeeping. There was a catch — the bot wasn’t completely automated. In what’s referred to in human-computer interaction as a “Wizard of Oz” experiment, Hwang was behind the scenes, feeding lines generated by ChatGPT into the bot.

After the experiment, Hwang and Won analyzed the chat logs of team conversations to determine how often participants offered ideas or arguments. They also asked participants to reflect on the experience.

“When we looked at participants’ actual behaviors, that’s where we started to see differences between men and women and how they were reacting when there was either a female agent or a male agent on the team,” she said.

“One interesting thing about this study is that most participants didn’t express a preference for a male- or female-sounding voice,” Won said. “This implies that people’s social inferences about AI can be influential even when people don’t believe they are important.”

When women were in the minority, they participated more when the AI’s voice was female, while men in the minority were more talkative but were less focused on tasks when working with a male-sounding bot, researchers found. Unlike the men, women reported significantly more positive perceptions of the AI teammate when women were the minority members, according to researchers.

“With only a gendered voice, the AI agent can provide a small degree of support to women minority members in a group,” said Hwang.

The research comprises two papers, one published in The Astrophysical Journal in April 2024, and one as yet unpublished that will be submitted to the same journal. The results will be presented at the 244th meeting of the American Astronomical Society, held June 9 through June 13 at the Monona Terrace Convention Center in Madison, Wisconsin. 

“Supermassive black holes in galaxy centers have millions-to-billions of times the mass of the Sun,” said Fan Zou, a graduate student at Penn State and first author of the papers. “How do they become such monsters? This is a question that astronomers have been studying for decades, but it has been difficult to track all the ways black holes can grow reliably.”

Supermassive black holes grow through a combination of two main channels. They consume cold gas from their host galaxy — a process called accretion — and they can merge with other supermassive black holes when galaxies collide.

“During the process of consuming gas from their hosting galaxies, black holes radiate strong X-rays, and this is the key to tracking their growth by accretion,” said W. Niel Brandt, Eberly Family Chair Professor of Astronomy and Astrophysics and professor of physics at Penn State and a leader of the research team. “We measured the accretion-driven growth using X-ray sky survey data accumulated over more than 20 years from three of the most powerful X-ray facilities ever launched into space.”

The research team used complementary data from NASA’s Chandra X-ray Observatory, the European Space Agency’s X-ray Multi-Mirror Mission-Newton (XMM-Newton), and the Max Planck Institute for Extraterrestrial Physics’ eROSITA telescope. In total, they measured the accretion-driven growth in a sample of 1.3 million galaxies that contained over 8,000 rapidly growing black holes.

“All of the galaxies and black holes in our sample are very well characterized at multiple wavelengths, with superb measurements in the infrared, optical, ultraviolet, and X-ray bands,” Zou said. “This allows for robust conclusions, and the data show that, at all cosmic epochs, more massive galaxies grew their black holes by accretion faster. With the quality of the data, we were able to quantify this important phenomenon much better than in past works.”

The second way that supermassive black holes grow is through mergers, where two supermassive black holes collide and merge together to form a single, even more massive, black hole. To track growth by mergers, the team used IllustrisTNG, a set of supercomputer simulations that model galaxy formation, evolution, and merging from shortly after the Big Bang until the present.

“In our hybrid approach, we combine the observed growth by accretion with the simulated growth through mergers to reproduce the growth history of supermassive black holes,” Brandt said. “With this new approach, we believe we have produced the most realistic picture of the growth of supermassive black holes up to the present day.”

The researchers found that, in most cases, accretion dominated black-hole growth. Mergers made notable secondary contributions, especially over the past 5 billion years of cosmic time for the most-massive black holes. Overall, supermassive black holes of all masses grew much more rapidly when the Universe was younger. Because of this, the total number of supermassive black holes was almost settled by 7 billion years ago, while earlier in the Universe many new ones kept emerging.

“With our approach, we can track how central black holes in the local universe most likely grew over cosmic time,” Zou said. “As an example, we considered the growth of the supermassive black hole in the center of our Milky Way Galaxy, which has a mass of 4 million solar masses. Our results indicate that our Galaxy’s black hole most likely grew relatively late in cosmic time.”

In addition to Zou and Brandt, the research team includes Zhibo Yu, graduate student at Penn State; Hyungsuk Tak, assistant professor of statistics and of astronomy and astrophysics at Penn State; Elena Gallo at the University of Michigan; Bin Luo at Nanjing University in China; Qingling Ni at the Max Planck Institute for Extraterrestrial Physics in Germany; Yongquan Xue at the University of Science and Technology of China; and Guang Yang at the University of Groningen in the Netherlands.

Funding from the U.S. National Science Foundation, the Chandra X-ray Center, and Penn State supported this work. The work was also made possible by the sharing of the IllustrisTNG simulation results with the scientific community.