This paper reports the discovery of a high-velocity star J07 ejected from globular cluster M15 approximately 21 million years ago, providing strong evidence for the presence of an IMBH constrained to within a few AU of the central region of M15.

In a paper published in Science Bulletin, the research teams led by Professor Shunmin He, Professor Runsheng Chen, and Professor Tao Xu from the Institute of Biophysics, Chinese Academy of Sciences, introduced TOAnnoPriDB—a comprehensive resource for annotating and prioritizing non-coding variants across the human genome. This represents the seventh publication from the NyuWa genome project. TOAnnoPriDB integrates trans-omic data from 147 public resources, including six databases previously developed by the team: NyuWa, NONCODE, NPInter, piRBase, SmProt, and LncVar. It features a framework for assessing the functional impact of variants and offers a user-friendly web interface. The database empowers researchers to prioritize and analyze variants, advancing studies on variant functions and disease-related research in humans.

Green hydrogen from water splitting has emerged as a critical energy vector with the potential to spearhead the global transition to a fossil fuel-independent society. The feld of catalysis has been revolutionized by single-atom catalysts (SACs), which exhibit unique and intricate interactions between atomically dispersed metal atoms and their supports. Recently, bimetallic SACs (bimSACs) have garnered signifcant attention for leveraging the synergistic functions of two metal ions coordinated on appropriately designed supports. BimSACs ofer an avenue for rich metal–metal and metal–support cooperativity, potentially addressing current limitations of SACs in efectively furnishing transformations which involve synchronous proton–electron exchanges, substrate activation with reversible redox cycles, simultaneous multi-electron transfer, regulation of spin states, tuning of electronic properties, and cyclic transition states with low activation energies. This review aims to encapsulate the growing advancements in bimSACs, with an emphasis on their pivotal role in hydrogen generation via water splitting. We subsequently delve into advanced experimental methodologies for the elaborate characterization of SACs, elucidate their electronic properties, and discuss their local coordination environment. Overall, we present comprehensive discussion on the deployment of bimSACs in both hydrogen evolution reaction and oxygen evolution reaction, the two half-reactions of the water electrolysis process.

Established in 2012, the New Sunshine Hospital School in China provides free educational support to hospitalized children aged 3 to 14 to address gaps in their education and development. In a recent article in ECNU Review of Education, researchers use this program as a case study to discuss and explore how and what contributes to the success of this educational support initiative in the hospital, offering insights to counter a global educational challenge.

In a ground-breaking first, researchers have for the first time prepared catalyst with excellent CO₂ cycloaddition catalytic performance for single-atom copper by utilizing the nano-constrained environment between the silica wall and the templating agent in mesoporous silica KIT-6. This strategy provides a new idea for the convenient preparation of single-atom catalysts.

Researchers developed a computational model to optimize melt crystallization—a low-energy method for producing ultra-pure dimethyl carbonate (DMC). The study reveals how natural convection shapes crystal layer and proposes heating strategies to improve efficiency, offering industry a sustainable path to high-purity materials.

The article utilizes the friction electromagnetic induction coupling mechanism to design a single fiber based Fibre-WBAN it converts the mechanical energy generated by the human body movement into electrical signals and uses the fiber coils to convert the low-frequency time-domain signals into high-frequency frequency-domain signals (40 MHz) for wireless data transmission.

A deep learning-based scheme is proposed for automated and efficient processing of teleseismic phases.

1. The validation with two teleseismic phases, PcP and PKiKP, demonstrate high detection accuracies and low picking errors.

2. Deep-learning picking of first peaks is more accurate than picking first breaks of teleseismic phases.

3. This proposed scheme would enhance mining of teleseismic phases and probing of Earth's interior structures and their dynamics.