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Physics-based AI could boost biomedical imaging and autonomous vehicle sensors

A research team led by UCLA and the University of Rochester has demonstrated a promising evolution of an imaging system designed to capture details within “complex media,” which scatter light, from depicting structures inside body tissue to seeing obstacles through heavy fog. The system uses physics-based machine learning to improve an existing imaging technique.

In tests with standard calibration images obscured by complex media, the new system more than doubled the signal-to-noise ratio compared with a previous generation of the technology. The system also created images in near real time—thousandths of a second. The findings are published in the journal Light: Science & Applications.

Chemists develop a molecular platform for the selective control of oxygen reaction pathways

Controlling how oxygen reacts is important for improving technologies such as batteries, fuel cells and environmentally sustainable chemical processes. A research team led by professor Seung Jun Hwang from KAIST’s Department of Chemistry has developed a molecular system capable of directing oxygen activation along a selected electron-transfer pathway.

By combining germanium with a molecular framework that can store and transfer electrons, the team established a design principle for selectively switching oxygen activation between two-and four-electron pathways. The results were published in Chem.

More connections can deepen polarization when social ties remain weak

Social networks, intended to bring people together, can actually increase polarization, new research finds, because while the links in the network may be plentiful, they’re probably weak. A research team including Cornell sociologist Michael Macy has found that while the growing number of international contacts enabled by modern communications technologies may indeed contribute to greater polarization, as shown in previous studies, the underlying mechanism does not necessarily depend on an increase in close friendships. Instead, weaker social ties appear to play a more significant role, as they are more likely to foster hierarchical structures shaped by social status.

“The most important argument in our paper is the polarizing effect of ‘status-driven dynamics’ involving weak ties,” said Macy, with “status” referring to whether an individual holds another in high or low esteem. “The importance lies in the distinction between structural and ideological polarization.”

Microscale roughness breakthrough defies 80 years of fluid dynamics

Logically, you would think a sleek surface has optimal aerodynamics—but recent research at Tohoku University turns this fundamental principle on its head. Applying an irregular microscale surface texture reduced the aerodynamic drag of a test model. The innovation has potential applications in the design of fuel-efficient vehicles. The study is published in the Journal of Fluid Mechanics.

For more than 80 years, a fundamental principle of fluid dynamics has held that smoother surfaces produce less aerodynamic drag. However, a research group led by associate professor Aiko Yakeno at the Institute of Fluid Science, Tohoku University, has overturned this long-standing assumption. By applying Distributed Micro-Roughness (DMR)—irregular microscale surface textures—to a test model, the team achieved the world’s first experimental demonstration of up to 43.6% aerodynamic drag reduction.

By reducing drag in this innovative way, researchers may be able to reduce fuel consumption and CO₂ emissions across aviation, automotive, marine and rail transportation in the future.

Detecting the body’s magnetic fields with a low-power Ramsey-based magnetometer

Our bodies generate extremely weak magnetic fields as electric currents flow through the heart, brain and other tissues. These signals are used in magnetocardiography and magnetoencephalography to assess heart function and brain activity, respectively. These fields can be detected at room temperature using diamond sensors containing nitrogen-vacancy (NV) centers, in which a carbon atom is replaced by a nitrogen atom adjacent to an empty lattice site.

However, conventional NV-center sensors typically require watt-level lasers to detect the extremely weak biomagnetic fields, which are usually below the picotesla level. These high-power lasers generate significant heat, limiting how close the sensor can be placed to biological tissue. Since biomagnetic fields rapidly weaken with distance, overcoming thermal and close-proximity challenges is essential for practical biomagnetic sensing.

A research team led by Professor Takayuki Iwasaki from the Department of Electrical and Electronic Engineering, School of Engineering, Institute of Science Tokyo, Japan, has developed a diamond quantum magnetometer using a low-power laser of just 210 mW, a light-trapping diamond waveguide and a compact microwave antenna. The new sensor limits its temperature rise to only 13 K while allowing it to be placed just 2 mm (0.08 inches) from the sample, enabling close-proximity biomagnetic measurements without compromising thermal safety.

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