To address this challenge, Professor Liu Rui's team from South China University of Technology introduces a novel quantitative method, cell-specific causal network entropy (CCNE), which analyzes gene-level causal relationships to infer distinct causal networks for individual cells and identify pre-transition states in complex biological systems.

A research paper by scientists at Nankai University presents a monolithic synaptic device that replicates and integrates tactile sensing and neuromorphic processing functions for in-sensor computing.

The new research paper, published on Aug. 19, 2025 in the journal Cyborg and Bionic Systems, reported a monolithic pressure-electronic-gated (PEG) neuromorphic device that replicates CT afferents, for low-threshold mechanosensation and neuromorphic information processing in the same device.

As the number of wireless applications and devices grows, higher standards for the quality of service and navigation performance of mobile networks are required. Numerous critical applications, including unmanned aerial vehicles, internet of things, digital twin, and military systems, require reliable communication and accurate navigation services. To meet these requirements, the development of the sixth generation (6G) network is necessary. 6G networks provide seamless 3-dimensional coverage in space–air–ground–sea area, as well as deep coupling of communication, sensing, and computation. 6G networks will be combined with low Earth orbit (LEO) satellites to construct a universal and intelligent integrated system of communication, sensing, and computing by utilizing the benefits of LEO satellites, such as miniaturization, modularity, large bandwidth, low latency, and wide area coverage. One of the critical construction tasks in this system is the integration of communication and navigation (ICAN), which can break the limitations of the global navigation satellite system, provide high-precision, robust navigation capability, and enable high- quality communication services.

Space manipulators play an important role in the on-orbit services and planetary surface operation whose reliability is a key issue. In the extreme environment of space, space manipulators are susceptible to a variety of unknown disturbances. Since it is difficult for the manipulator to be repaired immediately, once it fails, it will mean that it cannot complete the mission as expected, which may cause serious losses and dangers. How to have a resilient guarantee, i.e., the manipulator’s ability to resiliently recover and continue to complete tasks, in failure or disturbance is the core capability of its future development. The motion planning unit is used as the computing terminal of the manipulator’s joint motion trajectory. Compared with traditional motion planning, learning-based motion planning has gradually become a hot spot in current research. However, no matter what kind of research ideas, the single robotic manipulator is studied as an independent agent, making it unable to provide sufficient flexibility under conditions such as external force disturbance, observation noise, and mechanical failure.

The gravitational wave is a prediction of the general theory of relativity that can be detected by measuring the relative distance between two test masses (TM) along the geodesics. The TM is fixed by the cage and vent mechanism to avoid collision with the spacecraft cavity during launch. Once the drag-free spacecraft reaches its target orbit, the TM must be released by the grabbing positioning and release mechanism (GPRM) to the cage center of the inertial sensor in a limited amount of time. The capture of the TM by means of the electrostatic suspensions is crucial for the mission. However, the GPRM inevitably generates large release errors and the low electrostatic force makes the TM capture control a difficult task. Moreover, the experimental results of the LISA Pathfinder mission have shown that the TM release velocities were well higher than the ones expected. The previous robust sliding mode controller needs to be optimized.