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EV105/#457 Risk factors associated with overall survival of cervical cancer: a prospective cohort study in Western China comparing random survival forest and Cox proportional-hazards models

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International Journal of Gynecological Cancer 2024年 34卷 A140-A140页

作者： Zejia Mao Ling Long Yuan Li Hongji Wu Qiaoling Li Qianjie Xu Misi He Cong Zhang Haike Lei Dongling Zou Chongqing University Chongqing Shapingba China Department of Gynecologic Oncology Chongqing University Cancer Hospital and Chongqing Cancer Institute and Chongqing Cancer Hospital Chongqing Chongqing Shapingba China Chongqing Specialized Medical Research Center of Ovarian Cancer Chongqing China； Chongqing China Chongqing Medical University Chongqing China Chongqing Cancer Multi-Omics Big Data Application Engineering Research Center Chongqing University Cancer Hospital Chongqing Chongqing China Organoid Transformational Research Center Chongqing Key Laboratory of Translational Research for Cancer Metastasis and Individualized Treatment Chongqing University Cancer Hospital Chongqing Chongqing China

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Web Intelligence (WI) 3.0: in search of a better-connected world to create a future intelligent society

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Artificial Intelligence Review 2025年第9期58卷

作者： Kuai, Hongzhi Huang, Jimmy X. Tao, Xiaohui Pasi, Gabriella Yao, Yiyu Liu, Jiming Zhong, Ning School of Computer Science and Technology/School of Artificial Intelligence Chongqing University of Posts and Telecommunications Chongqing China Key Laboratory of Big Data Intelligent Computing Chongqing University of Posts and Telecommunications Chongqing China School of Information Technology York University North YorkON Canada School of Mathematics Physics and Computing University of Southern Queensland ToowoombaQLD Australia Department of Informatics Systems and Communication University of Milano-Bicocca Milano Italy Department of Computer Science University of Regina Regina Canada Department of Computer Science Hong Kong Baptist University Kowloon Tong Hong Kong Faculty of Engineering Maebashi Institute of Technology Gunma Maebashi Japan

Over the past two decades, Web Intelligence (WI) has emerged as a key field driving the evolution of AI in the connected world, addressing the demands of a future intelligent society. This paper provides a comprehensive review of WI’s contributions since its inception in 2000, spanning three distinct phases: Wisdom World Wide Web (WI 1.0, 2000–2009), Wisdom Web of Things (WI 2.0, 2010–2017), and Wisdom Web of Everything (WI 3.0, since 2018). For each phase, we examine key advancements, challenges, and future directions from the perspectives of both intelligent machines and human experts, highlighting significant societal impacts. To advance WI research, we propose a large language model-based learning framework for topic analysis and trend prediction. Moving beyond single-perspective approaches, we emphasize the Connected Intelligence Ecosystem defined by the HIGH5 scheme comprising one goal, two twins, three fundamentals, four functions, and five services that are realized through WI 3.0. This vision serves as a bridge from localized models to a global reference framework for addressing sustainability challenges in future societies. To illustrate the real-world implications of WI 3.0, we present case studies focusing on brain-inspired research, particularly in the intersection of brain intelligence, brain health, and brainternet-fostering interdisciplinary collaboration across diverse research communities. © The Author(s) 2025.

关键词： Intelligent computing

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Multi-view SVM Classification with Feature Selection

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Procedia Computer Science 2019年 162卷 405-412页

作者： Yuting Niu Yuan Shang Yingjie Tian School of Information Engineering Zhengzhou University Zhengzhou 450001 China Smart City Institute Zhengzhou University Zhengzhou 450001 China Supercomputer Center Smart City Institute Zhengzhou University Henan 450001 China Research Center on Fictitious Economy and Data Science Chinese Academy of Sciences Beijing 100190 China Key Laboratory of Big Data Mining and Knowledge management Beijing 100190 China School of Economics and Management University of Chinese Academy of Sciences Beijing 100190 China

With the rapid development of data mining technology, multi-view learning (MVL) has become a new research field, which has attracted wide attention of scholars at home and abroad. Multi-view learning is to combine multiple view data of the same entity for data classification, thereby improving learning performance. Previous multi-view research methods mainly concentrate on the relationship between different data views for classification problems. However, when the data is in high dimensions, it is necessary to perform feature selection in the multi-view data classification process. In this paper, we proposed a Multi-view Support Vector Machine Classification with Feature Selection (MSVMCFS) algorithm, which can not only classify multi-view data, but also select features for each view data in the process of classification. In the model, feature selection is performed by the l 1 norm sparsity regularization, and consistency and complementarity between the two views are maintained. To achieve the optimization goal, we adopt linear programming to solve the model. The experimental results on 30 binary datasets demonstrate the validity of the model.

关键词： multi-view learning classification feature selection sparsity regularization linear programming

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Recommending more suitable music based on users’ real context 14th

Recommending more suitable music based on users’ real conte...

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14th EAI International Conference on Collaborative Computing: Networking, Applications and Worksharing, CollaborateCom 2018

作者： Yang, Qing Zhan, Le Han, Li Zhang, Jingwei Bi, Zhongqin School of Electronic Engineering and Automation Guilin University of Electronic Technology Guilin541004 China Guangxi Cooperative Innovation Center of Cloud Computing and Big Data Guilin University of Electronic Technology Guilin541004 China Guangxi Key Laboratory of Trusted Software Guilin University of Electronic Technology Guilin541004 China College of Computer Science and Technology Shanghai University of Electronic Power Shanghai200090 China

ISBN: (纸本)9783030129804

Music recommendation is an popular function for personalized services and smart applications since it focuses on discovering users’ leisure preference. The traditional music recommendation strategy captured users’ music preference by analyzing their historical behaviors to conduct personalized recommendation. However, users’ current states, such as in busy working or in a leisure travel, etc., have an important influence on their music enjoyment. Usually, those existing methods only focus on pushing their favorite music to users, which may be not the most suitable for current scenarios. Users’ current states should be taken into account to make more perfect music recommendation. Considering the above problem, this paper proposes a music recommendation method by considering both users’ current states and their historical behaviors. First, a feature selection process based on ReliefF method is applied to discover the optimal features for the following recommendation. Second, we construct different feature groups according to the feature weights and introduce Naive Bayes model and Adaboost algorithm to train these feature groups, which will output a base classifier for each feature group. Finally, a majority voting strategy decides the optimal music type and each user will be recommended more suitable music based on their current context. The experiments on the real datasets show the effectiveness of the proposed method. © 2019, ICST Institute for Computer Sciences, Social Informatics and Telecommunications engineering.

关键词： Adaptive boosting

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Enhancing countries' fitness with recommender systems on the international trade network

arXiv

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arXiv 2019年

作者： Liao, Hao Wu, Xing-Tong Vidmer, Alexandre Huang, Xiao-Min Liu, Ming-Kai Zhou, Mingyang Zhang, Yi-Cheng National Engineering Laboratory for Big Data System Computing Technology Guangdong Province Key Laboratory of Popular High Performance Computers College of Computer Science and Software Engineering Shenzhen University Shenzhen518060 China Department of Physics University of Fribourg Fribourg1700 Switzerland

Prediction is one of the major challenges in complex systems. The prediction methods have shown to be effective predictors of the evolution of networks. These methods can help policy makers to solve practical problems successfully and make better strategy for the future. In this work, we focus on exporting countries' data of the international trading network. A recommendation system is then used to identify the products corresponding to the production capacity of each individual country, but are somehow overlook by the country. Then, we simulate the evolution of the country's fitness if it would have followed the recommendations. The result of this work is the combination combine these two methods to provide insights to countries on how to enhance the diversification of their exported products in a scientific way and improve national competitiveness significantly, especially for developing countries. Copyright © 2019, The Authors. All rights reserved.

关键词： Recommender systems

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Experimental Study on Flow Characteristics in a Compound Open Channel with Flexible Vegetation

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IOP Conference Series: Earth and Environmental Science 2021年第1期697卷

作者： Xiaoxiao Guo Hefang Jing Weihong Wang Juntao Wu Qiaoling Zhang Research Institute of Numerical Computation and Engineering Applications North Minzu University Yinchuan China School of Mathematics and Information Science North Minzu University Yinchuan China The Key Laboratory of Intelligent Information and Big Data Processing of Ningxia Province North Minzu University Yinchuan China

In order to study the effect of flexible vegetation for the flow in open channels with flood plains, a series of experiments were carried out in a laboratory flume with a two-stage floodplain. Four cases, i.e., dense parallel arrangement, normal parallel arrangement, sparse parallel arrangement and no vegetation condition, were designed with fixed water depth and discharge. By using three dimensional (3D) laser Doppler velocimeter (LDV) and other instruments, under the condition of the four cases,3D flow velocities, water level and turbulence intensity were measured, The experimental results show that, compared with the non-vegetation situation, the arrangement of grasses on the floodplain will increase the water surface gradient, hydraulic gradient and turbulence intensity to a certain extent.

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Accelerated placental aging mediated the association between prenatal exposure to per- and polyfluoroalkyl substances and small-for-gestational age newborns

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Ecotoxicology and Environmental Safety 2025年 299卷 118338页

作者： Fan, Yijun Guo, Liyan Gao, Chang Fang, Yuanyuan Zhou, Qiang Xia, Zhicai Wang, Chengrui Wang, Ruolan Lv, Jia Tao, Lin Fang, Mingliang Zhao, Mei Xu, De-Xiang Huang, Yichao School of Public Health and Center for Big Data and Population Health of IHM Anhui Medical University Hefei 230032 China Department of Gynecology and Obstetrics The Second Affiliated Hospital Anhui Medical University Hefei 230032 China Department of Clinical Laboratory The Second Affiliated Hospital Anhui Medical University Hefei 230032 China Xuancheng Center for Disease Control and Prevention Xuancheng 242099 China State Key Laboratory of Dampness Syndrome of Chinese Medicine The Second Affiliated Hospital of Guangzhou University of Chinese Medicine Guangzhou 510120 China Department of Environmental Science and Engineering Fudan University Shanghai 200438 China School of Nursing Anhui Medical University 230032 China Clinical Research Center Suzhou Hospital Anhui Medical University Suzhou 234099 China

Whether prenatal exposure to per- and polyfluoroalkyl substances (PFAS) is a risk factor for small-for-gestational-age (SGA) neonates remain elusive, yet even less is known on the role of premature placental aging in this potential adverse effect. In this analysis of 1046 maternal-infant dyads, 30 legacy and emerging PFAS were measured from maternal serum. Associations between (co-)exposure to PFAS and the incidence of SGA were determined using logistic regression, Bayesian Kernal Machine Regression (BKMR) and quantile-based g-computation (QGC) for single and mixture effect, respectively. Despite the legacy PFAS, prenatal exposure to short-chain emerging PFAS, including perfluorohexane sulfonic acid (PFHxS, per log 10 unit: OR=2.91, 95 %CI=1.63–5.27) and perfluoropentanoic acid (PFPeA, per log 10 unit: OR=3.02, 95 %CI=1.50–6.31) were associated with higher SGA odds. Co-exposure to these highly prevalent PFAS were associated with increased odds of delivering SGA infants, with both models showing emerging PFAS PFHxS and perfluorotridecanoic acid (PFTrDA) being the primary contributors. Further in a 1:2 case-control setting, it was found placental relative telomere length (TL) was shorter in mothers bearing SGA than those with AGA (0.82 vs 0.99, P = 0.001), showing negative association with SGA birth (OR: 0.33, 95 %CI: 0.14–0.76). Mediation analysis revealed that placental TL mediated 17.7 % of the relationship between PFHxS exposure and the risk of SGA birth, respectively. Prenatal PFAS exposure, especially the short-chain congeners, was positively associated with the odds of SGA, and the relationship was partially mediated by shortened placental TL, indicating a need for targeted health management in pregnant mothers at higher risk of SGA due to high PFAS exposure. © 2025 The Authors

关键词： Mediation analysis Mixture effect Per- and polyfluoroalkyl substance Placental aging Small-for-gestational age Telomere length

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Investigation of the Salinity Distribution of the Soil along West Main Canal in Ningxia, China

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IOP Conference Series: Earth and Environmental Science 2021年第1期697卷

作者： Juntao Wu Hefang Jing Weihong Wang Xiaoxiao Guo Xinxia Guo Research Institute of Numerical Computation and Engineering Applications North Minzu University Yinchuan China School of Mathematics and Information Science North Minzu University Yinchuan China The Key Laboratory of Intelligent Information and Big Data Processing of Ningxia Province North Minzu University Yinchuan China

As one of the main irrigation canals in Ningxia, West Main Canal plays a very important role in the irrigation of the land nearby the canal, such as farms, meadows, and tree farms. Because of the long-term use of the Yellow River water for irrigation, the soil salinization in this area become more serious. In this paper, the problem of soil salinization along the West Main Canal in Ningxia is taken as the research object. 82 sample points in the studied area are chosen and a total number of 164 soil samples are measured for the eight main salt ions and pH value. Correlation analysis and principal component analysis are employed to study the distribution of the soil salinity ions and pH value. In addition, two dimensional interpolation is applied to obtain the spatial distribution of the total saltiness. It can be found that Cl−, SO42−, Ca2+, Na+ and HCO3− are the main salt ions and the main soluble salts are NaCl, KCl, CaSO4, Na2SO4 and CaCl2 in the soil of the studied area. The spatial distribution of the total soil salt is mainly in the patterns of north high and south low, far high and near low, up high and down low.

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Insight into disinfection byproduct formation potential of aged biochar and its effects during chlorination

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Journal of environmental management 2022年 317卷 115437页

作者： Hailan Yang Shujing Ye Han Wang Chengyun Zhou Ting Xiong Yuanyuan Deng Qianmin Fu Guangming Zeng Zhuotong Zeng Xiaofei Tan Department of Dermatology Second Xiangya Hospital Central South University Changsha 410011 PR China College of Environmental Science and Engineering and Key Laboratory of Environmental Biology and Pollution Control (Ministry of Education) Hunan University Changsha 410082 PR China. College of Environmental Science and Engineering and Key Laboratory of Environmental Biology and Pollution Control (Ministry of Education) Hunan University Changsha 410082 PR China School of Resources Environment and Materials Guangxi University Nanning 530004 PR China. Institute of Big Data and Internet Innovation Hunan University of Technology and Business Changsha 410205 PR China. College of Environmental Science and Engineering and Key Laboratory of Environmental Biology and Pollution Control (Ministry of Education) Hunan University Changsha 410082 PR China. Electronic address: zengzhuotong@***. College of Environmental Science and Engineering and Key Laboratory of Environmental Biology and Pollution Control (Ministry of Education) Hunan University Changsha 410082 PR China. Electronic address: tanxf@***.

Biochar can achieve multiple benefits including solid waste management, polluted water remediation, carbon sequestration, and emission reduction. However, various environmental factors (such as temperature variations and dry-wet alternation) and microbial activity may lead to the fragmentation, dissolution, and oxidation of biochar. These accelerate the dissolution of biochar-derived dissolved organic matter (DOM) and then influence disinfection byproducts formation potential (DBPFP) throughout the water treatment process. In this paper, biochars from six biomass feedstocks with five aging processes were prepared, and the DBPFP of biochar and its derived DOM were first studied systematically. Different aging processes might increase the DBPFP of biochar by increasing DOM content and changing the fraction distribution of DOM derived from biochar. Especially, the DBPFP of biochar increased apparently with the chemical aging process. Coexisting with the environmental concentration of humic acid, even aged biochar showed the potential to reduce DBPFP and integrated toxic risk value of the mixed system. In this study, the DBPFP of biochar-derived DOM during the disinfection process is confirmed, and the results can give information to the selection of biomass feedstocks of biochar and its service life in the water treatment process.

关键词： Aged biochar Chlorination Disinfection byproducts Dissolved organic matter Integrated toxic risk value

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The role of climate and urbanization in compound meteorological event exposure in China’s megacities

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Climate Risk Management 2025年

作者： Liling Chu Chao Xu Yanwen Wang Chaoqing Huang Zhaoliang Zeng Yilin Li Yiqi Zhou Qian Wu Pingan Jiang Xusheng Gong Yujia Hong Chao He College of Resources and Environment Yangtze University Wuhan 430100 China College of Resources and Environment Xinjiang Agricultural University Urumqi 830052 China Xinjiang Key Laboratory of Soil and Plant Ecological Processes Urumqi 830052 China Xinjiang Engineering Technology Research Center of Soil Big Data Urumqi 830052 China School of Economics and Management China University of Geosciences Wuhan 430074 China School of Tourism and Culture Guangdong Eco-Engineering Polytechnic Guangzhou 510520 China State Key Laboratory of Severe Weather Chinese Academy of Meteorological Sciences Beijing 100081 China School of Geography and Ocean Science Nanjing University Nanjing 210023 China School of Resource and Environmental Sciences Wuhan University Wuhan 430079 China Hubei University of Science and Technology Xianning 437100 China Department of Real Estate and Construction Favulty of Architecture The University of Hong Kong 9990777 Hong Kong China National Science Library (Wuhan) Chinese Academy of Sciences Wuhan 430071 China

Compound precipitation and wind speed extremes (CPWE) pose significant threats to the sustainable development of urban areas. This study investigated the spatial evolution characteristics, potential population exposure risk, and multidimensional inequality of CPWE within nine urban agglomerations in China, each containing at least one city with a GDP exceeding one trillion yuan, utilizing spatiotemporal statistics and attribution analysis. The results indicated that the intensity of CPWE in these urban agglomerations decreased from southeast to northwest, and the population exposed to mild, moderate, severe, and extreme levels accounted for 58 %, 28.3 %, 11.4 %, and 2.3 % of the total, respectively. Changes in exposure risk were driven by climate effect (58.29 % ± 12.77 %), followed by population (32.15 % ± 6.20 %) and interaction effect (9.55 % ± 5.14 %). Pearl River Delta (PRD) and Yangtze River Delta (YRD), identified as particularly vulnerable, experienced an increase in CPWE intensity exceeding 0.015 /10a. An increase of approximately 0.62 × 10 4 people per decade was observed for exposure risk, with over 20 % of the population facing severe or extreme levels, mainly due to the climate effect. CPWE exposure risk was significantly unequal across various dimensions (spatial autocorrelation: Moran’s I  = 0.3798, P  = 0.001; Gini coefficient: 0.08–0.5). Areas characterized by high-risk and balanced development (e.g., PRD, YRD) exhibited lower inequality, whereas regions featuring low-risk and concentrated development (e.g., GPZ) demonstrated higher inequality. The climate effect was the predominant influence in the low-risk areas as well as most high-risk areas. These findings support the targeted implementation of appropriate climate adaptation policies to promote regional sustainable development.

关键词： Compound precipitation and wind speed extremes (CPWE) Population exposure risk Multiscale inequality Exposure attribution China’s megacities

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