Team studies beryllium-7 variations over Antarctic regions of the Southern Ocean

Findings help understanding of Earth’s atmospheric mixing

Research Organization of Information and Systems

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Schematic diagram. beryllium-7 produced by cosmic rays in the upper atmosphere is transported to near-ground levels via folding of the tropopause associated with low- and high-pressure systems, and is also transported near the surface in coastal regions by katabatic winds descending the slopes of the Antarctic continent.

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Credit: Naohiko Hirasawa from National Institute of Polar Research, Japan

A Japanese research team has studied the variations in beryllium-7 concentrations in the surface air over the Antarctic regions of Southern Ocean. Beryllium-7 is a radioactive isotope of beryllium produced by cosmic rays in the atmosphere. The team explored, over space and time, how the beryllium-7 is transported from the atmosphere to the Earth’s surface. Their goal was to better understand the mechanisms of atmospheric mixing on Earth.

Their research is published in the Journal of Geophysical Research: Atmospheres on October 14, 2025.

“We aimed to clarify where and by what atmospheric flows the radioactive isotope beryllium-7, produced in the stratosphere and upper troposphere, is transported to the Earth's surface. To achieve this, we undertook the collection of daily continuous data in the Antarctic region — something that had not been done before,” said Naohiko Hirasawa, National Institute of Polar Research, Research, Organization of Information and Systems.

Beryllium-7 is a rare isotope produced when high-energy cosmic rays collide with atoms in the atmosphere, mainly in the lower stratosphere and the upper troposphere. Immediately after its production, it attaches to nearby aerosol particles, allowing it to be transported through atmospheric circulation. High concentrations of beryllium-7 in the air indicate that air from the stratosphere has been transported down into the troposphere. By investigating the atmospheric circulation of beryllium-7 concentrations, researchers can better understand the mechanisms that drive air transport from the stratosphere through the troposphere to the surface of the Antarctic ice sheet.

The team gathered observations over three summers from 2014 to 2018, as part of the Japanese Antarctic Research Expedition. They examined the geographical characteristics of beryllium-7 concentrations over high latitudes in the Indian sector of the Southern Ocean, including two Japanese coastal stations. They collected aerosol particles using a glass fiber filter that trapped particles greater than 0.6 µm in diameter. The team conducted their experiments aboard the Japanese icebreaker Shirase, used for Antarctic expeditions.

They had several goals in undertaking the study. They wanted to describe the spatial distribution of beryllium-7 concentrations over a wider area of the Antarctic region than has been conducted in past studies. They also wanted to investigate variations in beryllium-7 concentrations in relation to synoptic‐scale atmospheric circulation. These are large-scale disturbances, spanning hundreds to thousands of kilometers, that typically move across the Antarctic region with a period of about one week. The team also wanted to examine diurnal variations in beryllium-7 concentrations associated with katabatic winds. These katabatic winds are winds that blow down the Antarctic ice sheet slope because of gravity. The team hopes their results could potentially be used to validate beryllium-7 transport models.

“The greatest challenge was detecting beryllium-7 at extremely low concentrations — a result of the short sampling duration and the long delay between collection and measurement — with sufficient precision to capture its variability. For this reason, each filter analysis required 8 to 12 hours,” said Hirasawa.

Their findings showed that variations in the beryllium-7 concentration were connected to synoptic-scale disturbances. These disturbances also deposit other stratospheric materials, like volcanic material from the troposphere, onto the Antarctic ice sheet. These stratospheric materials can be used as climatic markers in ice cores. The team’s findings in this study also contribute to decoding paleoclimate atmospheric circulation patterns in ice core investigations.

“We found that beryllium-7 is periodically transported down to near the surface through tropopause foldings associated with synoptic-scale low- and high-pressure systems. In addition, there was another mechanism in which katabatic winds blowing down the Antarctic ice sheet slopes entrained beryllium-7 present in the mid-troposphere over the ice sheet and transported it to coastal regions,” said Hirasawa.

The team noted other findings besides the beryllium-7 transport. “While beryllium-7 is supplied from the upper troposphere, another radioactive isotope, radon-222, is emitted from the land surface of continents through soil and rocks. By elucidating the transport processes of these two substances, we aim to deepen our understanding of the mechanisms of atmospheric mixing on Earth,” said Hirasawa.

The research team includes Naohiko Hirasawa from the National Institute of Polar Research, Research Organization of Information and System and SOKENDAI (The Graduate University for Advanced Studies); Taku Nakamura, Shigeki Tasaka, and Miyoko Miwa from Gifu University; Tetsuro Ojio from Nagoya City Science Museum; and Kyohei Yamada from National Institute of Polar Research, Research Organization of Information and System.

The research is funded by the Japanese Antarctic Research Expedition and the National Institute of Polar Research.

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About National Institute of Polar Research (NIPR)
The NIPR engages in comprehensive research via observation stations in Arctic and Antarctica. As a member of the Research Organization of Information and Systems (ROIS), the NIPR provides researchers throughout Japan with infrastructure support for Arctic and Antarctic observations, plans and implements Japan's Antarctic observation projects, and conducts Arctic researches of various scientific fields such as the atmosphere, ice sheets, the ecosystem, the upper atmosphere, the aurora and the Earth's magnetic field. In addition to the research projects, the NIPR also organizes the Japanese Antarctic Research Expedition and manages samples and data obtained during such expeditions and projects. As a core institution in researches of the polar regions, the NIPR also offers graduate students with a global perspective on originality through its doctoral program. For more information about the NIPR, please visit: https://www.nipr.ac.jp/english/

About the Research Organization of Information and Systems (ROIS)
ROIS is a parent organization of four national institutes (National Institute of Polar Research, National Institute of Informatics, the Institute of Statistical Mathematics and National Institute of Genetics) and the Joint Support-Center for Data Science Research. It is ROIS's mission to promote integrated, cutting-edge research that goes beyond the barriers of these institutions, in addition to facilitating their research activities, as members of inter-university research institutes.

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Journal

Journal of Geophysical Research Atmospheres

DOI

10.1029/2024JD043206 

(a) Altitude-time section of potential temperature concatenated for three locations: 37.5°E and 69°S for 10–14 February 2017, 49°E and 67.5°S for 15–24 February 2017, and 69°E and 66°S for 15–24 February 2017. Downward solid (broken) arrows indicate major (minor) increases in potential temperature, suggesting the decent of air with higher potential temperatures. (b) Time series of beryllium-7 concentration observed on the Shirase from 11 February to 4 March, corresponding to.

(a) Time series of beryllium-7 concentrations at site S17 for 5–12 January 2017, corresponding to. White (gray) bars indicate daytime (nighttime) beryllium-7  concentrations. The average concentration in the daytime (nighttime) was 3.85 (4.68) mBq/m3 with a standard deviation of 0.36 (0.54) mBq/m3, respectively. (b) Time series of wind speed (black line) and wind direction (solid circles) at site S17. Gray shading corresponds to nighttime sampling.

Credit

Naohiko Hirasawa from National Institute of Polar Research, Japan

 

Looking good isn’t everything: University of Illinois researchers assess AI method for processing medical images

Beckman Institute for Advanced Science and Technology

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Artificial intelligence has exploded in popularity in recent years, and many proponents are excited about its potential uses in medicine: for example, processing samples quickly or identifying markers of disease that may be missed by the human eye. However, is applying AI always the best option? 

Researchers found that while an AI method called virtual staining can improve the use of medical images in certain cases, in other situations it may actually decrease the ability to get useful information from those images. In general, they urge caution when deciding whether to apply AI to a given workflow, to ensure that it actually improves accuracy compared to other methods.

“The general conclusion is that AI can be a great tool — it does help in some cases — but you have to be a little bit cautious,” said Sourya Sengupta, a graduate student at the Beckman Institute for Advanced Science and Technology and this study’s lead author.

This study was conducted by researchers in the Center for Label-free Imaging and Multiscale Biophotonics, which aims to improve imaging technologies for clinical and research applications by developing new imaging methods and algorithms. In addition to Sengupta, CLIMB researchers Phuong Nguyen, Frank Brooks, Yang Liu and Mark Anastasio all collaborated on this project.

Most of us have had a medical image taken during a doctor’s appointment, such as an ultrasound, MRI or X-ray. These essential tools help researchers and clinicians diagnose diseases, test new treatments and monitor patient health. Another common class of medical images are microscopy images, which allow clinicians to get a closer look at magnified tissue and cell samples.

To improve a microscopy image’s contrast — for example, to make a certain part of a cell stand out so that clinicians can analyze its features — the tissue or cell samples are often stained using dyes or other chemicals. While widely used, staining can be time-intensive and may damage the cells. 

Label-free imaging is an alternative to staining in which chemicals are not added to the sample. Instead, researchers use natural properties of biological materials to make observations and create images. For example, measuring the different ways light passes through transparent objects like cells gives us information about cell density and growth. 

However, this method also has drawbacks. Label-free images still tend to have less contrast than stained images, which can make it difficult to identify key features. To improve the usefulness and reliability of label-free images, there has been recent interest in a new method called virtual staining. 

In the virtual staining process, a computational model analyzes a label-free image and predicts what the image would look like stained. Ideally, this would result in an image with the high contrast of a stained image, but produced much more quickly and without the potential for chemically damaging the sample. However, it is important to confirm these virtually stained images are truly accurate and useful for biological discoveries and clinical applications.

“In medicine or in drug discovery, taking images is not the end goal,” Sengupta said. “In biomedical imaging, we always think in terms of a task: a biological or clinical application that the images are meant to serve. So we started asking: these computationally generated images may look real, but do they actually help with the real task?”

One of the biggest challenges in answering this kind of question is simply having enough data. Researchers often need large sets of paired images — one from label-free imaging and the other from fluorescent staining — to train and test various AI models. Fortunately, Liu’s team recently developed the Omni-Mesoscope, a powerful high-throughput imaging system that can capture tens of thousands of cells at different states within minutes, creating large, high-quality datasets. These datasets provided the foundation for testing how virtually stained images perform in real-world analytical tasks.

The researchers tested how virtually stained images performed compared to label-free images and stained images in two tasks. First, the images were used in a segmentation task: a process in which a neural network identifies individual cell nuclei and crops them to each be their own picture. Like cropping a photo, this allows researchers and clinicians to hone in on the most important parts of the image. 

Secondly, researchers used the images in a cell classification task, in which the network identified what stages different cells were in after a drug treatment. This task has applications for monitoring drug effectiveness in research and in disease treatment. 

A comparison of label-free (first column), virtually stained (middle columns) and fluorescent stained (last column) images of two cells. The cell in the bottom row was treated with a drug, while the cell in the top row was not. 

For both tasks, researchers assessed the performance of different networks when using each type of image. The researchers wanted to know if the relative success of each image type would change depending on the properties of the network being used, so they repeated the tasks using five different networks.

Many networks perform similar tasks, but some networks may be better than others at representing complex functions or relationships depending on how the network is programmed to learn. These networks are called high-capacity networks. The networks used in this study had a range of capacities, so the researchers could see whether capacity impacted how the networks used the virtually stained images. 

When processed by low-capacity networks, the virtually stained images performed much better than the label-free images. However, with high-capacity networks, this was not the case. When applied to the segmentation task, the virtually stained and label-free images performed about the same when processed by high-capacity networks. When applied to the cell classification task, however, the virtually stained images performed substantially worse. In other words, when using a high-capacity network to analyze your images, you would be more likely to get accurate information if you used label-free images rather than virtually stained ones.

This result is consistent with a concept called the data processing inequality, which states that processing any image (such as by virtual staining) cannot increase the information contained in that image, Sengupta said. This is similar to touching up a family photograph: you can blur the background to make the people stand out, but no amount of edits will open the eyes of someone who was blinking when the shutter clicked.

Low-capacity networks are likely helped by virtually stained images because processing can emphasize important information. In contrast, high-capacity networks, which can already pick out complex relationships from the label-free images, are not helped by virtual staining. The virtual staining process may even remove information that is crucial for certain tasks, which may explain why virtually stained images performed worse than label-free images in the cell classification task. 

While AI has potential applications in many areas of healthcare, Sengupta reminds clinicians, researchers and members of the public interested in this technology to be cognizant of its limitations. If AI is being used for a specific task, it is important to verify that it will actually be beneficial in that situation.

“Even if AI is a buzzword now, you have to be a little bit cautious when applying it in sensitive domains like biomedical imaging and healthcare,” Sengupta said. “In a lot of cases, AI is very useful, but it might not always be.”

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Journal

Biomedical Optics Express

DOI

10.1364/BOE.576061 

Method of Research

Experimental study

Subject of Research

Cells

Article Title

On the utility of virtual staining for downstream applications as it relates to task network capacity

 

SwRI identifies security vulnerability in EV charging protocol

Researchers publish common vulnerabilities and exposures report related to ISO 15118

Southwest Research Institute

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SwRI identified security vulnerabilities in the Signal Level Attenuation Characterization (SLAC) protocol governing the connection process between a supply equipment communication controller (SECC) and electric vehicle communication controller (EVCC). SwRI developed a machine-in-the-middle (MitM) device to tap into the appropriate line in the charger cable. Researchers injected signals that led to full control over the communications channel. By spoofing a second charger with superior attenuation, an attacker can bridge the charger connection to intercept traffic.

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Credit: Southwest Research Institute

SAN ANTONIO — November 18, 2025 — Southwest Research Institute identified a security vulnerability in a standard protocol governing communications between electric vehicles (EV) and EV charging equipment. The research prompted the Cybersecurity & Infrastructure Security Agency (CISA) to issue a security advisory related to the ISO 15118 vehicle-to-grid communications standard.

Through internal research, a team of SwRI engineers spoofed signal measurements between an EV and EV supply equipment (EVSE), leading to CISA’s publication of a Common Vulnerabilities & Exposures (CVE) advisory: https://www.cisa.gov/news-events/ics-advisories/icsa-25-303-01.

“It’s important to note that this vulnerability comes from the requirements in an industry standard, meaning it can affect a variety of vehicle manufacturers,” said Mark Johnsn, an SwRI engineer who led the research. “We hope this will encourage manufacturers to continue working to adopt ISO 15118-20 and to adopt technologies such as public key infrastructure in the EV charging space that would better protect consumers.”

The research explored vulnerabilities in the Signal Level Attenuation Characterization (SLAC) protocol. The ISO 15118 communication standard relies on SLAC to identify which charging station a particular vehicle is connected to within a charger network. This process involves sending a signal from the vehicle to the chargers, which then respond with a measure of signal quality.

After identifying security deficiencies within the SLAC process, SwRI’s research team developed a machine-in-the-middle (MitM) attack to test if communications between vehicles and chargers could be compromised. The researchers successfully modeled the attack using simulators before replicating the attack between vehicles and charging stations.

Using the MitM device to tap into the appropriate line in the charger cable, the researchers injected signals that led to full control over the communications channel, demonstrating that that the EV charging process could be manipulated or halted using the MitM attack.

“It took some time to develop the software for the attack, but running the attack was surprisingly consistent,” said Kyle Owens, an engineer who supported the project. “The research demonstrates how a malicious actor can trick an EV into establishing a connection by responding to the vehicle's SLAC signal with an artificial measurement.”

Newer components of the standard, such as ISO 15118-20, require the use of Transport Layer Security (TLS), which limits the potential impacts of this vulnerability. Although such security protocols demand more computational power, they are necessary to protect future generations of vehicles. SwRI researchers note that this vulnerability can be leveraged to confirm the presence of such countermeasures or to conduct related security research.

The project used a direct connection to confirm the existence of the vulnerability. However, the SwRI researchers also demonstrated the attack wirelessly, via electromagnetic induction, in a benchtop simulation. SwRI is considering future research to further explore the attack’s feasibility through wireless technologies.

The SwRI’s High Reliability Systems Department performs a variety of cybersecurity services for the automotive industry, helping to identify cyberthreats to ground vehicles, transportation infrastructure, and automotive embedded systems.

For more information, visit https://www.swri.org/markets/automotive-transportation/automotive/automotive-software-electronics/electric-vehicle-cybersecurity-services.