In recent years, di-silicate (Yb₂Si₂O₇) has been extensively studied due to its outstanding performance and is regarded as one of the most promising materials for environmental barrier coatings (EBCs). However, the decomposition and volatilization of Yb₂Si₂O₇ during the thermal spraying process present a challenge to the stability of these coatings. Teak, renowned for its exceptional mechanical strength, corrosion resistance, and durability, provides a new direction for EBC development with its distinctive layered structure. A research team has skillfully utilized the decomposition characteristics of Yb₂Si₂O₇ during spraying, precisely controlling the composition and nanostructure of the Yb₂Si₂O₇ coatings to emulate the layered structure of teak. This has resulted in the development of a novel environmental barrier coating (EBC). This innovative design not only marks a breakthrough in coating technology but also introduces new opportunities for advancements in the field of EBC protection.

To foster a sustainable public health environment, a research team from The Hong Kong Polytechnic University (PolyU) Department of Civil and Environmental Engineering has collaborated with experts from international universities, utilising big mobility data and advanced sensor technology to study urban air pollution. Their study has highlighted the significance of daily travel patterns, and race and ethnicity in assessing differences in residents’ exposure to air pollution, offering new insights for authorities worldwide when developing air pollution mitigation measures. The findings have been published in the international journal Nature Cities.

A new study published in Forest Ecosystems highlights the growing wildfire risk posed by standing dead trees in Yellowstone National Park. Using advanced machine learning and spatial analysis, the researchers mapped tree mortality and assessed the vulnerability of nearby infrastructure, offering valuable insights for fire management and wildfire mitigation efforts in high-risk areas.

In this issue of hLife, the team led by Prof. Min Wang from Ocean University of China systematically mined and characterized the diversity of viral reverse transcriptases from global metagenomic datasets. Viral reverse transcriptases are not only encoded by pathogenic retroviruses; their vast diversity is hidden in the genomes of ubiquitous bacteriophages, which are widely distributed in the human gut microbiomes and various ecosystems on Earth. This study is expected to shed light on their critical roles in microbial ecology and evolution, offering valuable insights for future antiviral strategies and biotechnological applications.

Recently, Professor Xiaoli Huang from Jilin University, Dr. Dmitrii Semenok from Center for High Pressure Science and Technology Advanced Research, and Professor Tian Cui from Ningbo University et al., successfully synthesized a novel hydride superconductor, A15-La₄H₂₃ through the high-temperature and high-pressure techniques.

In a paper published in National Science Review, an international team of researchers introduced the one-core-neuron system (OCNS), a “small model” framework designed to tackle the inefficiency of “large models”. By utilizing a single core neuron, OCNS achieves comparable or superior performance in time-series forecasting while reducing parameter requirements to a fraction of those in existing “large models”. This approach highlights the potential of small models in efficient deep learning and more sustainable AI applications.

Cancer is a major public health problem and represents substantial disparities worldwide. This study reported estimates for 36 cancers across 185 countries by incidence, mortality, 5-year prevalence, mortality-to-prevalence ratio (MPR), and mortality-to-incidence ratio (MIR) to examine its association with human development index (HDI) and gross national income (GNI). Data were collected from the GLOBOCAN 2020. MPR and MIR were calculated by sex, age group, country, and cancer type and then summarized into totals. Segi’s population and global cancer spectrum were used to calculate age- and type-standardized ratios. Correlation analyses were conducted to assess associations. Results showed that breast cancer was the most diagnosed cancer globally. Low- and middle-income countries had high MPR and MIR. Cancers of esophagus, pancreas, and liver had the highest ratios. Males and the older population had the highest ratios. HDI and GNI were positively correlated with incidence and mortality but negatively correlated with MPR/MIR. Substantial disparities in cancer burden were observed among 36 cancer types across 185 countries. Socioeconomic development may contribute to narrowing these disparities, and tailored strategies are crucial for regional- and country-specific cancer control.

In the research, they model the message adversary training process as a cooperative MARL problem, where each adversary obtains the local state of one message sender, then outputs  stochastic actions as message perturbations for each message to be sent to other teammates.