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Zhongshan Daxue Xuebao/Acta Scientiarum Natralium Universitatis Sunyatseni

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( Vol 65 , Issue 01 ) | 15 May 2026

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( Vol 44 , Issue 01 ) | 28 Mar 2025

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Zhongshan Daxue Xuebao/Acta Scientiarum Natralium Universitatis Sunyatseni

Zhongshan Daxue Xuebao/Acta Scientiarum Natralium Universitatis Sunyatseni (ISSN:2097-0137) is a monthly peer-reviewed scopus-indexed journal from 1980, from 2001 to Present. The publisher of this journal is Journal of Zhongshan University. ASNUS is committed to gathering and disseminating excellent research achievements. The journal welcomes all kind of research/review/abstract papers regarding Multidisciplinary subjects.

Aim And Scope

Zhongshan Daxue Xuebao/Acta Scientiarum Natralium Universitatis Sunyatseni

1. Agricultural Science / Agri Engineering

2. Electrical & Telecommunication Engineering

3. Computer Science & Engineering

4. Civil and Architectural Engineering Department

5. Food Process Engineering Unit

6. Chemical Engineering Department

7. Mechanical & Material Engineering Division

8. Department of Physics

9. Department of Mathematics

10. Earth & Planetary Sciences

11. Accounting & Financial Studies

12. Social Sciences

13. Economic

14. Environmental Science

15. Linguistics

16. Business Management

17. Law

18. Biological Sciences

19. Public Health

20. Marketing Studies

21. Fishery

22. Zoological Studies

23. Human Resource Management (HRM)

24. Historical Studies

25. Materials Science

26. Global Business

27. Plant Biology (Botany)

28. Psychological Studies

Latest Journal

Zhongshan Daxue Xuebao/Acta Scientiarum Natralium Universitatis Sunyatseni

Fully asynchronous distributed optimization with linear convergence over directed networks

We consider the distributed optimization problem, the goal of which is to minimize the sum of local objective functions over a directed network. Though it has been widely studied recently, most of the existing algorithms are designed for synchronized or randomly activated implementation, which may create deadlocks in practice. In sharp contrast, we propose a fully asynchronous push-pull gradien

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Nonconvex low-rank matrix recovery models and methods for spectral compressed sensing:An overview

Because of the contradiction between the spatial and temporal resolution of remote sensing images (RSI) and quality loss in the process of acquisition, it is of great significance to reconstruct RSI in remote sensing applications. Recent studies have demonstrated that reference image-based reconstruction methods have great potential for higher reconstruction performance, while lacking accuracy

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The spatio-temporal characteristics of tropical cyclone precipitation based on high-resolution data

Tropical cyclones (TCs) significantly impact the Caribbean Lesser Antilles, often causing severe wind and water damage. Traditional flood hazard assessments simplify TC rainfall as single-peak, short-duration events tied to specific return periods, overlooking the spatial–temporal variability in rainfall that TCs introduce. To address this limitation, a new user-friendly tool incorporates

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Analysis on typical design rainstorm hydrographs of central cities in the Guangdong-Hong Kong-Macao Greater Bay Area

Understanding the driving factors and assessing the risk of rainstorm waterlogging are crucial in the sustainable development of urban agglomerations. Few studies have focused on rainstorm waterlogging at the scale of urban agglomeration areas. We used the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) of China as a case study. Kernel density estimation (KDE) and spatial autocorrelation analy

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Hyperspectral estimation of soil conductivity of different land use types in lakeside oasis of Bosten Lake in Xinjiang

To more accurately understand the soil salinity of different land use types in the lakeside oasis of Bosten Lake, Xinjiang, three methods of competitive adaptive reweighted sampling(CARS), successive projection algorithm(SPA), and competitive adaptive reweighted-successive projection algorithm(CARS-SPA) were applied to screen the characteristic bands of soil conductivity hyperspectral data of d

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