Dual optimization and control of VLEO relay systems via multiplexed/classical multimodel MPC
Peer-Reviewed Publication
Updates every hour. Last Updated: 25-Oct-2026 05:16 ET (25-Oct-2026 09:16 GMT/UTC)
With the unique advantages that very low Earth orbit (VLEO) satellites have demonstrated in fields such as high-resolution remote sensing, the contradiction between the demand for large-volume data downlink and the extremely short visibility windows of ground stations has become increasingly prominent. Sun-synchronous orbit VLEO satellites typically have only one to two ground station passes per day, each lasting only a few minutes, far from sufficient to meet the high-throughput data downlink requirements generated by missions such as high-resolution imaging and video surveillance. However, existing relay architectures are unsuitable for small satellites due to constraints in mass, power consumption, and latency; low-rate terminals can only provide basic telemetry; conventional proportional–integral–derivative controllers struggle to maintain accuracy under nonlinear and strong disturbance environments; and nonlinear model predictive control imposes excessive computational burdens. Therefore, how to coordinately optimize the resource allocation and control strategies of VLEO satellites and relay constellations to achieve an effective balance between data transmission efficiency and onboard computational capability has become a key technical challenge in supporting high-capacity VLEO missions.
MIT researchers developed a handheld device that can gently collect living cells from specific locations to test for ovarian and other cancers. The technique could be used to catch cancers earlier and more effectively, and to create personalized treatments.
Researchers at Fraunhofer IAF have developed a broadband distributed amplifier chip based on the institute’s proprietary InGaAs-on-Si HEMT technology. It achieves a gain of 11 ± 2 dB between 4 and 420 GHz and is ideally suited for use in data centers, measurement systems and sensors. Along with other new developments in the field of high-frequency electronics, Fraunhofer IAF will present the chip from October 4 to 9, 2026, at European Microwave Week in London (Booth B35).
A South Korean research team has developed an eco-friendly ammonia synthesis process that significantly reduces carbon emissions through innovative separation membrane technology. The Korea Institute of Energy Research (KIER) found that a palladium membrane selectively transports hydrogen ions in water across the membrane and subsequently demonstrated the practical feasibility of this mechanism through application to the ammonia synthesis process.
Circularly polarized light (CPL) carries spin angular momentum information and holds great promise for magnetic recording, spin optical communication, biological sensing and quantum computation. Conventional CPL detectors rely heavily on bulky and complex external optical components, which restrict device integration and miniaturization. Chiral organic semiconductors possessing an intrinsic capability for direct CPL discrimination, have emerged as promising candidates for CPL detectors. However, their development faces an intrinsic trade-off between charge carrier mobility and absorption dissymmetry factor.
Encouragingly, tremendous efforts have been devoted to resolving this contradiction, contributing to the development of a series of high-performance chiral organic semiconductors and thereby CPL detectors. Now, writing in Science Bulletin, researchers at the Institute of Chemistry, Chinese Academy of Sciences, systematically review representative progress of chiral organic semiconductors with a particular emphasis on the planarity-helicity dilemma and spectral tailoring. The review further highlights advances in CPL detectors and emerging applications, and discusses key challenges and future opportunities toward high-performance, miniaturized, and integrated CPL detection technologies.University of Missouri researchers have developed an artificial intelligence-powered tool called MeLSI (Metric Learning for Statistical Inference) that helps scientists identify subtle but important changes in the gut microbiome that traditional methods often miss. By pinpointing the specific bacteria driving biological differences, MeLSI provides a clearer understanding of how the microbiome influences health and disease.