A collaborative team led by Ravi Radhakrishnan of the School of Engineering and Applied Science and Jake Brenner and Jacob Myerson of the Perelman School of Medicine at the University of Pennsylvania has unraveled the mathematics of a 500-million-year-old protein network that acts like the body’s bouncer, “deciding” which foreign materials get degraded by immune cells and which are allowed entry. “This discovery enables us to design therapeutics the way you’d design a car or a spaceship—using the principles of physics to guide how the immune system will respond—rather than relying on trial and error,” says Brenner.

A new cooling technology could significantly improve the energy efficiency of data centers and high-powered electronics while reducing water use associated with cooling. By passively removing heat through evaporation, it offers a promising alternative to traditional cooling systems.

University of São Paulo researchers are developing an aircraft equipped with sensors that can detect and measure the concentrations of carbon dioxide and methane in the environment; the project was presented at FAPESP Week France in Toulouse.

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.

The management of liquid manure generated by livestock farming is an environmental problem that affects soil, water and air when there is a high concentration. The Solid State Chemistry Group at the Universitat Jaume I in Castelló, coordinated by Professor Juan Bautista Carda, has created an innovative method for treating and recovering liquid manure using laser technology.

The new system involves separating the solid and liquid parts using laser irradiation according to specific parameters to obtain high value-added products. The liquid part is then treated again with laser irradiation to adapt it for agricultural or industrial use.