The ability to precisely predict movements is essential not only for humans and animals, but also for many AI applications — from autonomous driving to robotics. Researchers at the Technical University of Munich (TUM) have now discovered that artificial neural networks can perform this task better when trained with biological data from early visual system development.

Submarine canyons are large, kilometer-deep gorges on the seafloor along continental margins that transport sediments, nutrients, and carbon from offshore regions into the deep sea. Geoscientists Professor Anne Bernhardt of Freie Universität Berlin and PD Dr. Wolfgang Schwanghart of the University of Potsdam have uncovered a surprising insight using a global statistical model: The primary factor influencing the formation of submarine canyons is the steepness of the seafloor – not, as commonly assumed, the role of rivers and where they transport sediment into the ocean. Their new study, “Seafloor Slopes Control Submarine Canyon Distribution: A Global Analysis,” has just been published in the scientific journal “Science Advances”.

Soft electronics, which are designed to function under mechanical deformation (such as bending, stretching, and folding), have become essential in applications like wearable electronics, artificial skin, and brain-machine interfaces. Crystalline silicon is one of the most mature and reliable materials for high-performance electronics; however, its intrinsic brittleness and rigidity pose challenges for integrating it into soft electronics. Recent research has focused on overcoming these limitations by utilizing structural design techniques to impart flexibility and stretchability to Si-based materials, such as transforming them into thin nanomembranes or nanowires. This review summarizes key strategies in geometry engineering for integrating crystalline silicon into soft electronics, from the use of hard silicon islands to creating out-of-plane foldable silicon nanofilms on flexible substrates, and ultimately to shaping silicon nanowires using vapor–liquid–solid or in-plane solid–liquid–solid techniques. We explore the latest developments in Si-based soft electronic devices, with applications in sensors, nanoprobes, robotics, and brain-machine interfaces. Finally, the paper discusses the current challenges in the field and outlines future research directions to enable the widespread adoption of silicon-based flexible electronics.

In order to solve the difficult problem of pigeon robots in outdoor flight altitude control, Prof. Zhendong Dai's team at the School of Electromechanics, Nanjing University of Aeronautics and Astronautics (NUAA), has started an in-depth cooperation with the Brain-Computer Interface and Fusion Intelligence team at the Institute of Automation, Chinese Academy of Sciences (CASIA). For the first time, the research team has expanded the research on flight control of pigeon robots from indoor to outdoor real flight environments, and proposed a quantitative neural stimulation method based on the Locus Coeruleus (LoC) of pigeon midbrain; the research team systematically explored the effects of three key parameters, namely stimulation frequency (SF), stimulation interval (ISI), and stimulation cycle (SC) on the flight altitude control of pigeon robots.