Table of Content

21 August 2024, Volume 46 Issue 4

Previous Issue   

Invited Special Paper

Land cancer and its control

HUANG Jianping, FU Li, LI Changyu, HUANG Jiping

2024, 46(4):  239-246.  doi:10.3969/j.issn.0253-9608.2024.04.001

Asbtract ( 652 )   PDF (5581KB) ( 132 )  

Related Articles | Metrics

Earth’s health condition is getting worse due to global warming, urbanization, and desertification, significantly threatening the ecological security and the sustainable development of society. The land that cannot produce adequate oxygen through photosynthesis will gradually lose water storage capacity, resulting in positive feedback that warming and drying reinforce each. By regarding the Earth as a living body, we propose the concept of land cancer and develop a method to diagnose its health condition. Also, we constructed the cancer land index (CLI), which indicates that cancerous land accounts for 53% of the global land area. Land cancer starts from deserts and drylands with the lowest oxygen production, and from urban centers and concentrated industries with the highest oxygen consumption, then gradually expands to the surrounding areas. The whole process is analogous to the spread of cancer cell in the human body, manifesting the deterioration of Earth’s health. Our study thoroughly investigates the concept of land cancer and detects areas of cancerous lands, which offer mitigation suggestions for natural and anthropogenic cancerous lands. The
objective is to strive for early detection of land cancer and prevent its expansion, thereby protecting Earth’s health.


Review Article

Advances in machine learning model for fatigue life prediction

DENG Yang, DAI Chunchun, WANG Ruijin, ZHU Fangyan, LENG Jiantao, CHANG Tienchong

2024, 46(4):  247-260.  doi:10.3969/j.issn.0253-9608.2024.04.002

Asbtract ( 2177 )   PDF (2848KB) ( 1638 )  

Related Articles | Metrics

Accurate prediction of fatigue life has long been a critical challenge in the design and development of advanced equipment. In recent years, artificial intelligence (AI) models have introduced a new paradigm for fatigue life prediction, offering promising solutions. In particular, the integration of existing knowledge into AI models can significantly enhance their training and predictive capabilities. This paper provides a comprehensive review of the current state of research on knowledge-guided and data-driven models of fatigue life prediction, highlighting their respective strengths and weaknesses, and outlining fthe challenges and possible future perspectives.




Artificial intelligence in cultural heritage conservation

CHENG Yuan , HUANG Jizhong, ZHANG Yue, PENG Ningbo

2024, 46(4):  261-270.  doi:10.3969/j.issn.0253-9608.2024.04.003

Asbtract ( 3305 )   PDF (2449KB) ( 1467 )  

Related Articles | Metrics

Artificial intelligence (AI) is revolutionizing the field of cultural heritage conservation. This paper comprehensively reviews the current applications of AI in various aspects of cultural heritage conservation. In the field of cultural heritage digitization, AI techniques such as semantic segmentation of laser point clouds have significantly improved the efficiency and accuracy of digitization processes. For cultural heritage recognition and management, deep learning-based image segmentation and knowledge graphs provide support for intelligent management. In the area of cultural heritage monitoring and detection, machine learning can autonomously analyze the condition of cultural heritage from environmental parameters and non-destructive testing data, enabling early warning of deterioration. In virtual restoration and display, AI technologies are optimizing methods and experiences from multiple perspectives, including image processing, geometric reconstruction, and interactive presentation. The results show that AI is fundamentally changing the concepts, methods, and technologies of cultural heritage conservation, significantly improving efficiency and accuracy. This review provides a reference for further exploration of AI-enabled pathways in cultural heritage conservation, contributing to the advancement of technological innovation and the deep integration of cultural heritage conservation with modern technology. 




Advances in the application of artificial intelligence in environmental science

LAO Jiayi, WANG Xiaoyan, SHI Bo, WANG Bin, JIAO Zheng

2024, 46(4):  271-280.  doi:10.3969/j.issn.0253-9608.2024.04.004

Asbtract ( 1087 )   PDF (1681KB) ( 3027 )  

Related Articles | Metrics

The rapid development and high efficiency of artificial intelligence (AI) have made it increasingly popular in the field of scientific research. Over the past decade, there has been an exponential growth in the application of AI in environmental science. One of the main advantages of using artificial intelligence is its ability to efficiently analyze and process large amounts of data, which is a crucial issue faced by environmental science research. Therefore, the application of artificial intelligence can greatly promote the development of environmental science and engineering. This paper reviews the latest applications of artificial intelligence in the field of environmental science, discusses its advantages and existing problems, as well as the opportunities and challenges it brings to environmental science.




Science for the Future

From Moiré patterns to twistronics

ZHU Hongwei

2024, 46(4):  281-284.  doi:10.3969/j.issn.0253-9608.2024.04.005

Asbtract ( 611 )   PDF (3227KB) ( 238 )  

Related Articles | Metrics

The structure of materials is ever-changing, hiding the mysteries of the materials world. The article starts with the common Moiré patterns in daily life, introduces the concept of Moiré superlattices and the rich physical information they contain. The development of twistronics based on two-dimensional Moiré superlattices have achieved a wonderful fusion of materials science, physics, and topology.




Progress

Methods, applications and prospects of haploid induction in plants

YANG Yanming, WANG Na

2024, 46(4):  285-298.  doi:10.3969/j.issn.0253-9608.2024.01.012

Asbtract ( 2508 )   PDF (4204KB) ( 1838 )  

Related Articles | Metrics

Haploid induction largely improves the efficiency of breeding. Haploid production mainly consists of in vitro gametophytic tissue culture and in vivo chromosome elimination. In this review, we focus on various strategies for in vivo haploid induction, along with recent research progresses and practical applications. Additionally, we provide an overview of the potential mechanisms underlying key haploid inducers, with a particular emphasis on the centromeric protein CENH3 mediated haploid induction.




Searching for beyond-the-Standard-Model fundamental particles through gravitational radiation

AN Yu , GE Xianhui

2024, 46(4):  299-305.  doi:10.3969/j.issn.0253-9608.2024.01.014

Asbtract ( 459 )   PDF (2755KB) ( 266 )  

Related Articles | Metrics

The detection of gravitational waves in 2016 has galvanized physicists in their pursuit of gravity research, affirming the validity of black hole theories and Einstein’s General Relativity, while spurring investigations into new physics under extreme conditions to refine existing frameworks. Black hole superradiance theory posits that unconventional particles could be generated in the vicinity of black holes, thereby challenging and extending the boundaries of the Standard Model. Although the Standard Model successfully accounts for known particles and the three fundamental interactions, the quest for “beyond-the-Standard-Model” phenomena remains a pivotal endeavor among physicists. This abstract explores the potential emergence of novel, beyond-the-Standard-Model particles, analogously to “gravitational atoms”, and introduces prospective methods utilizing gravitational wave detections for such particle searches.





Pathological mechanism and treatment methods of heart failure with preserved ejection fraction#br#

SONG Jiaxin, SHEN Shutong, ZHOU Qiulian, GAO Juan

2024, 46(4):  306-316.  doi:10.3969/j.issn.0253-9608.2023.04.016

Asbtract ( 276 )   PDF (2293KB) ( 295 )  

Related Articles | Metrics

Heart failure with preserved ejection fraction (HFpEF) affects about half of all patients with heart failure worldwide. The prevalence rate continues to grow with aging population year by year, while HFpEF has a high mortality rate. However, the pathogenesis of HFpEF is complex, and there is still lack of effective treatment. With the research progress in recent years, this review aims to elaborate and discuss the pathological mechanism of HFpEF and current treatment methods, providing an insight into developing novel therapeutic strategies for improving HFpEF.