Researchers from Tsinghua University and Henan Normal University developed a dedicated data analysis framework for the Silicon Strip Detector Telescopes (SSDTs) of the Compact Spectrometer for Heavy-IoN Experiments (CSHINE). Based on a modular architecture design, the framework integrates core analysis steps—including detector calibration, particle identification, and track reconstruction—into a unified system through C++ classes, effectively addressing the technical challenges of processing complex SSDT signals. Its robust performance was demonstrated through the successful analysis of light-charged particles in the 25 MeV/u ⁸⁶Kr + ¹²⁴Sn experiment conducted at the first Radioactive Ion Beam Line in Lanzhou, allowing for precise extraction of physical observables, including energy, momentum, and particle type. Through the optimization of track recognition algorithms with the utilization of reconstructed physical data, including effective physical event counts and energy spectra, the research team significantly enhanced the track recognition efficiency, achieving a remarkable rate of approximately 90%. This framework provides a standardized and reusable technical solution for SSDT-based detector systems.

Researchers at Tianjin University have developed LineGen, a physics-guided method combining ordinary differential equations and a time-embedded U-Net, to generate super-resolution load data (SRLD) for power distribution systems. Published in Engineering, the approach addresses limitations in high-frequency data collection by achieving a 1000-fold resolution enhancement—significantly surpassing prior deep learning methods—while offering traceable physical interpretability for improved grid management and reliability.

Researchers at Shenzhen University have developed a novel self-sensing steel fiber-reinforced polymer  composite bar (SFCB) that integrates distributed fiber-optic sensors (DFOS) for real-time monitoring of cracks and mechanical behavior in reinforced concrete members. This innovative approach, detailed in a recent study published in Engineering, aims to enhance the durability and safety of civil infrastructure by providing a more accurate and reliable method for structural health monitoring.

In the face of rising urbanization and food insecurity, a new study published in Engineering explores the potential of urban aquaponics to enhance food security and reduce environmental impacts. The research, led by Qiuling Yuan and Fanxin Meng from Beijing Normal University, provides a comprehensive framework for assessing the sustainability of aquaponics systems in urban areas, selecting Beijing as a case study. The findings suggest that urban aquaponics can significantly improve water efficiency and local food self-sufficiency while reducing energy consumption and carbon emissions through optimized strategies.

A new study in Engineering explores the optical properties of a high-entropy alloy (HEA) made from five noble metals—Au, Ag, Cu, Pd, and Pt—revealing its potential for use in mid-infrared metasurfaces through experimental determination of complex permittivity and analysis of absorption/emission characteristics.

A new study in Engineering presents a coordinated planning framework for power systems with high renewable energy (RE) penetration, introducing the concept of Renewable Energy Power-Flow Density (RE-PFD) to track RE transmission pathways through internal loads, external exports, and storage losses. Developed by researchers from Xi’an Jiaotong University, the model integrates transmission network and energy storage system (ESS) planning to address RE variability, ensuring efficient grid operation and compliance with green power trading requirements across interconnected systems.

In a recent study published in Engineering, researchers have developed an exact algorithm for placement optimization in mixed-cell-height (MCH) circuits, addressing key challenges in modern chip design such as non-overlapping constraints, voltage drain drain (VDD)/voltage source substrate (VSS) alignment, and minimum implantation area rules. The work presents a mixed-integer linear programming (MILP) model and a Benders decomposition (BD)-based approach to minimize placement cost while enhancing space utilization, validated through numerical experiments on benchmark datasets to demonstrate its efficiency for practical circuit design applications.