In recent years, rapidly advanced space technology has resulted in a growing number of objects in orbit, including both operational and decommissioned spacecraft, as well as space debris, which pose potential threats to China’s on-orbit spacecraft. To ensure the safe operation of spacecraft in near-Earth and high-orbit environments, a key research focus in the field of space technology is the high-resolution and high-accuracy detection and perception of environmental objects under strong backlight conditions. Such capabilities are critical for providing timely early warnings to on-orbit spacecraft. However, a plethora of studies have demonstrated marked challenges in imaging dark and weak targets under strong light backgrounds. It is essential to analyze the challenges of current backlight imaging technologies, summarize the working principles of existing backlight detection methods, and explore future development trends.

Relevant technological advancements in recent years have established solar sailing as an attractive propulsion system for terrestrial and interplanetary space missions, particularly missions that require low-thrust propulsion for long periods of time. The initial stages in designing solar sail missions involve a thorough analysis of possible transfer trajectories. Traditional approaches primarily focus on deterministic scenarios where the spacecraft dynamics is precisely defined and fully characterized. Whereas, space trajectories are inevitably subject to various sources of uncertainty, including modeling errors in the dynamics, inaccurate measurements, and unpredictable environmental effects, such as fluctuations in solar irradiance. These uncertainties necessitate the development of robust control strategies that can effectively handle stochastic effects. In recent years, reinforcement learning (RL) offers a promising framework for addressing optimization problems characterized by significant uncertainty, which can be challenging to handle using traditional methods. Meanwhile, deep reinforcement learning (DRL) utilizes neural networks (NNs) to approximate complex policies, i.e. control laws. 

Einstein’s general theory of relativity reveals that spacetime can be warped by mass and energy. As a conjecture in this context, the evolution of space-time curvature affected by gravitation will propagate through the vast universe like ripples. There remains a wealth of mysteries about astrophysics that have not been explored yet, and these “ripples” called gravitational waves may revolutionize the investigation for this. Space-based gravitational-wave observations, which broadly adopt heliocentric, geocentric, or libration-point architectures, can extend the scope to celestial bodies that generate valuable millihertz frequency waves and escape the Earth-bound noise. The heliocentric gravitational-wave detection relying on laser interferometry faces dual challenges: 1) the attitude errors couple into the interferometric arm-length measurements, potentially corrupting the picometer-level displacement sensitivity, making the attitude accuracy exceptionally rigorous, while 2) the ultra-long interferometric arms (and thus million-kilometer-scale intersatellite communication distances) introduce significant communication delays. As a key to space-based gravitational-wave observations, the past few years have witnessed the development of attitude-orbit control technique, and numerous control methodologies have sprung up for various space missions. However, current communication delay models and their corresponding compensation methods prove inadequate for heliocentric gravitational-wave detection scenarios. Additionally, in line with adaptive SMC, there are few investigations on attitude-orbit coordinated control for heliocentric gravitational-wave detection spacecraft formation. 

As we venture deeper into space and establish bases and orbital stations on celestial bodies, it is imperative to develop sustainable space transportation methods that minimise propellant usage. Currently, the most common method for Earth-Mars transfers is through chemical propulsion systems. While the chemical propulsion system is well established, it has several drawbacks, including low efficiency, high propellant mass requirements, thermal limitations, and operational complexity. Momentum exchange tethers, which, in theory, can operate without the need for any propellant, offer an innovative alternative to these propulsion systems. Especially, in a symmetrical tether, the COM lies at the centre of the length. If both the equal mass payloads are released at the same time, then the orbit of the tether does not change. Additional delta-v can be generated by the libration (oscillation) or rotation of the tethers, which can be induced by a motor facility. Though there are various investigations into space tethers, there is a gap in the use of symmetrical tethers for interplanetary transfers. 

With the long-term on-orbit operation of the China Space Station, using nanosatellite swarms for cooperative observation of its external structures has become an important technical direction for enhancing in‑orbit monitoring capabilities. However, the space station itself has a non‑spherical complex geometry (e.g., protruding structures such as modules and docking ports) and may perform attitude maneuvers (e.g., sun‑pointing) during orbital flight, making it a dynamic obstacle with both intricate shape and rotational motion relative to the nanosatellites. Traditional artificial potential field obstacle avoidance methods mostly simplify obstacles as spheres or ellipsoids, which cannot accurately characterize the composite geometric features of the space station, and usually ignore the obstacle's own rotational motion. This leads to difficulties in constructing the repulsive potential field, limited maneuvering space, and, more critically, a lack of rigorous theoretical proof to guarantee closed-loop system stability and collision avoidance. Therefore, developing a nanosatellite formation control method that can handle rotating non‑spherical obstacles while providing strict stability guarantees is of significant theoretical importance and engineering value for ensuring safe fly-around and efficient cooperative observation in the vicinity of the space station.

A new study examines how pre-service L2 English teachers manage student reluctance during microteaching sessions. Using conversation analysis, it shows how novice teachers use explanatory accounts, including smiles, wait time, and gradual nomination, to reduce participation pressure. The findings suggest that microteaching is a valuable space for pre-service teachers to develop classroom interactional competence and sensitive turn-allocation skills before entering real classrooms as future language educators.

This report presents the first documented case of an extraosseous Ewing’s sarcoma (ES) arising primarily in the retropharyngeal space of an adult. A 59-year-old female presented with progressive dysphagia and acute stridor, initially mimicking a retropharyngeal abscess. However, intraoperative findings showed no pus, and further immunohistochemistry and genetic testing confirmed ES with CD99 positivity and EWSR1 rearrangement. Despite multimodal considerations, the disease was extensive at diagnosis, and the patient deteriorated rapidly, passing away within two months.