Deep neural networks are a type of artificial intelligence (AI) that imitate how human brains process information, but understanding how these networks “think” has long been a challenge. Now, researchers at Kyushu University have developed a new method to understand how deep neural networks interpret information and sort it into groups. The study addresses the important need to ensure AI systems are accurate and robust and can meet the standards required for safe use.

Plastic pollution is a growing problem in Japan, prompting cleanup efforts to recover plastic litter from water bodies. However, research on recovery rates from different river basins remains limited. In a recent study, researchers from Japan conducted a nationwide analysis of plastic litter recovery in over 100 river basins, shedding light on the impact of climate change, population density, and natural disasters. Their findings will help inform future cleanup strategies and improve plastic management.

Ferrocene is a key molecule for developing molecular machines. However, it readily decomposes on the surface of flat noble metal substrates, marking a significant challenge. Now, for the first time, researchers stabilized ferrocene by linking it with ammonium salts and trapping them in a molecular film made up of cyclic crown ether molecules. The ammonium-linked molecule performs reversible lateral sliding motion upon the application of electrical voltage, representing the world's smallest molecular machine.

Copper-oxide (CuO₂) superconductors, such as Bi₂Sr₂CaCu₂O_8+δ (Bi2212), have unusually high critical temperatures. Optical reflectivity measurements of Bi2212 have shown that it exhibits strong optical anisotropy. However, this has not been studied through optical transmittance measurements, which can offer more direct insights into bulk properties. Now, researchers have elucidated the origin of this optical anisotropy through ultraviolet and visible light transmittance measurements of lead-doped Bi2212 single crystals, enabling a more precise investigation into its superconductivity mechanisms.

The performance of a magnetic fusion device is greatly affected by the turbulent transport in a magnetically confined plasma. Establishing a turbulent transport model that accurately predicts the transport of energy and particles caused by plasma turbulence is a critical research issue in developing fusion reactors. A research group led by Associate Professor Shinya Maeyama of the National Institute for Fusion Science and Professor Mitsuru Honda of the Graduate School of Engineering, Kyoto University, has successfully improved the predictive accuracy of turbulent transport models for fusion plasmas using a data science method called multi-fidelity modeling. Multi-fidelity modeling is a methodology that combines a large number of low-fidelity data with a small number of high-fidelity data to make the overall prediction more accurate. This method enables the combination of advantages of the predictability of physics-based simulation and the quantitativeness of experimental data. It is expected to help predict the performance of future fusion reactors and improve their design.

Researchers at Nagoya University in Japan have uncovered in anglerfish a specialized motor neuron population for the first dorsal fin used for “fishing”. When the first dorsal fin evolved from a swimming and buoyancy aid to a hunting tool, the motor neurons shifted their position in the central nervous system. The findings have implications for understanding the potential of evolutionary processes of vertebrates, including humans.

Scientists unearth a clue to the molecular mechanisms involved in N₂O reduction by deep-sea hydrothermal vent bacteria.

An Osaka Metropolitan University-led team analyzed the amino acids that affect the formation of spores in a bacterium that causes food poisoning, Clostridium perfringens, and identified serine as an amino acid that inhibits spore formation.

In a study recently published in the journal Nano Letters, published by American Chemical Society, researchers from Nano Life Science Institute (WPI-NanoLSI), Kanazawa University, Kanazawa, Japan, used frequency-modulated atomic force microscopy to reveal the submolecular structure of microtubule (MT) inner surface and visualize structural defects in the MT lattice, providing valuable insights into the complex dynamic processes that regulate microtubule function.

Deep meditation is often described as a ‘timeless’ state, but this depiction seems to contradict the continuous alertness meditators report. In a recent paper, Dr. Akiko Frischhut from Sophia University, Japan, offers a coherent conceptualization of deep meditation and introduces the ‘Extended Now Interpretation’ to resolve this contradiction. Her analysis could lead to deeper insights into how time is experienced, both in fringe states of consciousness and in everyday life.