Traditional server-based datacenters suffer from low resource utilization, insufficient hardware scalability, insufficient resource usage elasticity, and low fault tolerance. With the ever-increasing network speed and processing power in hardware controllers, physically disaggregating the coupled resources in a server has been a promising trend for building next-generation Datacenters, as it effectively addresses the limitations of server-based datacenters.

Non line of sight (NLOS) imaging achieves imaging of occluded objects by analyzing the reflection and scattering of relay surfaces. Deep learning methods are mainly used to restore two-dimensional hidden scenes and face challenges in reconstructing complex real-world scenes. To solve the problems, a research team led by Hao Liu and Mingliang Xu published their new study in Frontiers of Computer Science on 15 May 2026.

Existing research has focused on trajectory similarity computation under centralized data storage. However, in the real world, trajectories are often collected and held by multiple distinct entities that form a data federation. Due to commercial and legal restrictions, direct data sharing among these entities may be prohibited, which renders existing centralized methods incapable of supporting similarity computation over trajectory data federation.

A preclinical study published in Translational Exercise Biomedicine (ISSN: 2942-6812), an official partner journal of International Federation of Sports Medicine (FIMS), provides the first comprehensive map of how skeletal muscle adapts in the weeks and months following hemorrhagic stroke, revealing that different muscles remodel on different timelines (DOI: 10.1515/teb20260008). The findings suggest that rehabilitation programs may need to be timed to specific post-stroke windows to effectively leverage the muscle's natural plasticity for functional recovery.

Modern biomedical research increasingly demands advanced imaging capabilities in aspects such as resolution, throughput, and minimal invasiveness. To overcome the limitations of conventional single-modality microscopy, Professor Peng Xi’s team at Peking University developed a highly integrated multimodal fluorescence-phase microscopy (MFPM) system. Unifying structured illumination and differential phase contrast within a wide-field architecture, it reconstructs five modalities using ten raw frames, providing a versatile multidimensional imaging solution across various biological scenarios.

This study presents a scalable dual-band hydrochromic optical modulator that uses water and humidity to switch information across visible, mid-infrared, and chemical spectral channels. By integrating a porous polymer with a low-emissivity layer, the device enables multi-level anticounterfeiting and encryption with strong transmittance and emissivity modulation. Its reversible response, flexible format, and durability under cycling, heat, ultraviolet (UV), and saltwater exposure support practical security applications.