This study presents a machine learning approach to estimate the top-of-atmosphere (TOA) shortwave radiation flux from Deep Space Climate Observatory / Earth Polychromatic Imaging Camera (DSCOVR/EPIC) satellite observations. 

Recently, a collaborative research team led by Professor Yong-Qiang Li of Shandong University and Professor Yanmei Yang of Shandong Normal University systematically investigated the physical binding mechanisms between enzymes and the photosensitizer chlorin e6 (Ce6), and proposed a catalytically enhanced strategy for photodynamic therapy (PDT). The study demonstrated that the extent of positively charged regions on the enzyme surface could be served as a reliable indicator for evaluating and predicting the enzyme’s binding affinity to Ce6. Based on this criterion, the authors further developed catalase-Ce6 nanoconjugates (CAT-Ce6 NCs) exhibiting excellent stability and potent photodynamic antibacterial activity. The CAT-Ce6 NCs effectively remodeled hypoxic pathological microenvironments and eradicated bacteria, thereby promoting the advancement of catalysis-augmented PDT of bacterial infections. The aforementioned study, titled "Deciphering the Physical Binding Mechanism of Enzyme–Photosensitizer Facilitates Catalysis-Augmented Photodynamic Therapy," was published in the journal Research.

Heavy-ion collisions involve the collision of positively charged nuclei of heavy elements at nearly the speed of light. These collisions create a special state of matter called the quark-gluon plasma (QGP), accompanied by intense magnetic fields, resembling the early universe. However, the evolution of these magnetic fields over time has been hard to track. In this study, researchers review the recent experimental efforts to study the time-dependent evolution of magnetic fields generated in these collisions.