Nature 2025 science city ranking: six of top 10 in China, Qingdao is 31 between Munich and Berlin

https://www.nature.com/nature-index/supplements/nature-index-2025-science-cities/tables/overall

https://en.people.cn/n3/2025/1118/c90000-20391615.html

The newly released “Nature Index 2025 Science Cities” supplement shows that the number of Chinese cities in the global top ten rose from five in 2023 to six in 2024, marking the first time China holds a majority in the rankings.

The supplement draws on the Nature Index database, which tracks research articles published from 2015 to 2024. Its analysis uses “Share”, a fractional count reflecting institutional contribution to publications, as the primary metric, with time-series data adjusted to 2024 levels. Each city’s Share is calculated by summing the contributions of all affiliated institutions located within that city.

According to the Nature Index, the world’s leading science cities overall are: Beijing, Shanghai, New York metropolitan area (U.S.), Boston metropolitan area (U.S.), Nanjing (China), Guangzhou (China), San Francisco Bay Area (U.S.), Wuhan (China), Baltimore-Washington metropolitan area (U.S.), and Hangzhou (China).

Further analysis shows that Chinese cities hold a strong advantage in chemistry, physical sciences, and earth and environmental sciences, leading the global rankings in all three fields. Notably, Chinese cities claimed all of the top ten positions in chemistry for the first time. In the other two subject areas, they secured six of the top ten spots, with Beijing ranking first worldwide across all three domains.

European cities in the ranking start at 19 (London), followed by Zurich (28), Cambridge (29), Munich (30) and Berlin (32), following Qingdao at position 31.

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RamEx: high-throughput microbial ramanome analyses with accurate quality assessment

https://www.cas.cn/syky/202602/t20260226_5102870.shtml

https://doi.org/10.1186/s40168-026-02339-3

A research team at the CAS Qingdao Institute of Bioenergy and Bioprocess Technology has developed RamEx, an integrated analysis framework for Ramanome big data. This platform, tailored to the characteristics of Raman spectroscopy data, establishes a one-stop workflow from data reading and standardized preprocessing to downstream data mining, centered on automated quality control algorithms and efficient parallel computing processes. It also demonstrates a systematic analysis of microbial metabolomical heterogeneity and metabolic pattern differentiation at the single-cell level.

Raman genomics deep analysis can track the dynamic changes in the composition of macromolecules such as lipids, proteins, and nucleic acids in different cells, thus revealing the differentiation and succession patterns of microbial metabolic states at the population scale with single-cell precision. This provides new research ideas and technical pathways for understanding the functional organization and environmental adaptation mechanisms of complex communities.

RamEx removes spectral noise in Raman-based microbial cell sorting

http://english.cas.cn/newsroom/research-news/202602/t20260224_1151116.shtml

https://link.springer.com/article/10.1186/s40168-026-02339-3

Scientists from the CAS Qingdao Institute of Bioenergy and Bioprocess Technology have developed a novel computational tool, RamEx, designed to resolve the computational bottleneck in high-throughput microbial Ramanomics.

RamEx streamlines the full Ramanomic analysis pipeline, from data preprocessing and automated quality control to advanced data mining. An Iterative Convolutional Outlier Detection (ICOD) algorithm tackles spectral noise in an unsupervised manner to dynamically identify and eliminate spectral artifacts, ensuring high-quality input for downstream analysis.

The platform’s performance was validated using diverse datasets, including pathogenic bacteria, probiotics, and yeast fermentation systems. Notably, RamEx successfully captured phenotypic heterogeneity in genetically identical yeast cells by detecting subtle metabolic fluctuations and tracking the dynamic accumulation of intracellular macromolecules, including lipids, proteins, and nucleic acids.

Qingdao Port achieves fully unmanned operation of a container ship

https://japanese.cri.cn/2026/02/21/ARTI1771656131487329

The “Zhifei,” China’s first commercially operational smart container ship, accurately docked at a berth at the automated wharf in Qingdao Port, using unmanned autonomous navigation mode. This marks the first time that China has achieved an unmanned operation of a container ship, including navigation, berthing, and operation.

After the “Zhifei” container ship arrived at its designated location, the vacuum suction cups installed in its vacuum automatic mooring system powerfully attracted the hull, firmly securing it to the berth in less than 30 seconds, without any manual mooring work. The terminal’s fully automated loading and unloading equipment then operated simultaneously, and China’s A-TOS (Atelier Terminal Smart Management System) and A-ECS (Analytical Equipment Control System) worked together to precisely coordinate equipment such as automated cranes and automated guided vehicles at millisecond speeds, completing the container loading and unloading process.

The Zhifei is equipped with smart navigation core system, and as China’s first smart cargo ship for commercial operation, it features three navigation modes: manned, remotely controlled, and unmanned autonomous navigation.

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