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Journal of environmental Sciences 2024年第8期142卷 269-278页

作者： Ying Lu Se Wang Yifan Shen School of environmental Science and Engineering Collaborative Innovation Center of Atmospheric Environment and Equipment TechnologyJiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution ControlNanjing University of Information Science and TechnologyNanjing 210044China

The frequent detection of pharmaceutical compounds in the environment has led to a growing awareness,which may pose a major threat to the aquatic environment.In this study,photodegradation(direct and indirect photolysis)of two different dissociation states of fluoxetine(FLU)was investigated in water,mainly including the determination of photolytic transition states and products,and the mechanisms of indirect photodegradation with·OH,CO_(3)^(*-)and NO_(3)^(*).The main direct photolysis pathways are defluorination and C–C bond cleavage.In addition,the indirect photodegradation of FLU in water is mainly through the reactions with·OH and NO_(3)^(*),and the photodegradation reaction with CO_(3)^(*-)is relatively difficult to occur in the water environment.Our results provide a theoretical basis for understanding the phototransformation process of FLU in the water environment and assessing its potential risk.

关键词： Fluoxetine Photochemical mechanism Direct photolysis Free radical reaction DFT

Path signature-based XAI-enabled network time series classification

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Science China(Information Sciences) 2024年第7期67卷 91-106页

作者： Le SUN Yueyuan WANG Yongjun REN Feng XIA Department of jiangsu collaborative innovation center of atmospheric environment and equipment technology(CICAEET) Nanjing University of Information Science and Technology School of Computing Technologies Royal Melbourne Institute of Technology

Classifying network time series(NTS) is crucial for automating network administration and ensuring cyberspace security. It enables the detection of anomalies, the identification of network attacks,and the monitoring of performance issues, thereby providing valuable support for network protection and optimization. However, modern communication networks pose challenges for NTS classification methods.These include handling large-scale and complex NTS data, extracting features from intricate datasets, and addressing explainability requirements. These challenges are particularly pronounced for complex 5G networks. Notably, explainability has become crucial for the widespread deployment of network automation for 5G networks and beyond. To tackle these challenges, we propose a path-signature-based NTS classification model called recurrent signature(Recur Sig). This innovative model is designed to overcome the time-consuming feature selection problem by utilizing deep-learning(DL) techniques. Additionally, it provides a solution for addressing the black-box issue associated with DL models in network automation systems(NAS) by incorporating an explainable classification approach. Extensive experimentation on various public datasets demonstrates that Recur Sig outperforms existing models in accuracy and explainability. The results indicate its potential for application in cyberspace security and automated network management, offering an explainable solution for network protection and optimization.

关键词： network time series classification explainable artificial intelligence path signature automated network management recurrent neural network

Evaluating quality of motion for unsupervised video object segmentation

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Optoelectronics Letters 2024年第6期20卷 379-384页

作者： CHENG Guanjun SONG Huihui jiangsu Key Laboratory of Big Data Analysis technology Jiangsu Collaborative Innovation Center on Atmospheric Environment and Equipment TechnologyNanjing University of Information Science&TechnologyNanjing 210044China12

Current mainstream unsupervised video object segmentation(UVOS) approaches typically incorporate optical flow as motion information to locate the primary objects in coherent video frames. However, they fuse appearance and motion information without evaluating the quality of the optical flow. When poor-quality optical flow is used for the interaction with the appearance information, it introduces significant noise and leads to a decline in overall performance. To alleviate this issue, we first employ a quality evaluation module(QEM) to evaluate the optical flow. Then, we select high-quality optical flow as motion cues to fuse with the appearance information, which can prevent poor-quality optical flow from diverting the network's attention. Moreover, we design an appearance-guided fusion module(AGFM) to better integrate appearance and motion information. Extensive experiments on several widely utilized datasets, including DAVIS-16, FBMS-59, and You Tube-Objects, demonstrate that the proposed method outperforms existing methods.

关键词： Evaluating quality of motion for unsupervised video object segmentation

Recent progress in carbene-catalyzed fluoroalkylation

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Science China Chemistry 2024年第8期67卷 2448-2460页

作者： Bei Zhang Xuan Zhang Jian Wang jiangsu Key Laboratory of atmospheric environment Monitoring and Pollution Control Collaborative Innovation Center of Atmospheric Environment and Equipment Technology School of Environmental Science and Engineering Nanjing University of Information Science and Technology School of Pharmaceutical Sciences Tsinghua University

The fluoroalkyl fragment plays a vital role in various fields such as pharmaceuticals and materials science, and has a significant impact on human life not only on the present but also in the future. The insertion of fluoroalkyl groups into the chemical skeletons can cause considerable alternations in the chemical, physical and biological properties of molecules, which has attracted numerous scientists from different fields. This review focuses on N-heterocyclic carbene(NHC)-catalyzed fluoroalkylation reactions, providing a detailed analysis and summary of the achievements in the past two decades. Many successful examples clearly indicate that NHCs can catalyze the tranformation of fluoroalkylation reagents with various electronic characteristics, whether electrophilic, nucleophilic, or radical precursors. Herein, the fluoroalkylation reactions are classified based on different catalytic modes of NHCs: Lewis base catalysis, Umploung catalysis, radical catalysis and others. Meanwhile, by refining and systematically studying the contribution of NHC catalysis in fluoroalkylation reactions, this review is expected to provide valuable insights and enlightenment for related fields.

关键词： fluoroalkylation N-heterocyclic carbene radical catalysis

Climatic drivers of the Canadian wildfire episode in 2023

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atmospheric and Oceanic Science Letters 2024年第4期17卷 23-28页

作者： Yihan Hu Xu Yue Chenguang Tian jiangsu Key Laboratory of atmospheric environment Monitoring and Pollution Control Collaborative Innovation Center of Atmospheric Environment and Equipment TechnologySchool of Environmental Science and EngineeringNanjing University of Information Science&Technology(NUIST)NanjingChina

2023年5月加拿大发生极端野火事件并持续4个月时间.野火污染物排放对当地和下风向的空气质量造成了严重影响.本文对驱动此次野火事件的气象因子和相关大尺度环流进行了探究.研究表明,此次极端野火排放的二氧化碳相较往年同期增长了0.37G... 详细信息

2023年5月加拿大发生极端野火事件并持续4个月时间.野火污染物排放对当地和下风向的空气质量造成了严重影响.本文对驱动此次野火事件的气象因子和相关大尺度环流进行了探究.研究表明,此次极端野火排放的二氧化碳相较往年同期增长了0.37Gt (527.1%).受罗斯贝波频散影响,同期加拿大中西部区域出现持续的位势高度正异常,促进气流下沉并引发局地高温,中西部区域5-6月最高温平均上升8.11℃,部分区域甚至超过10℃,导致野火排放的显著增长.受有利地形和泛北极地区快速增暖的影响,预期未来加拿大中西部发生极端野火的概率可能会显著上升.

关键词：野火气候变化遥相关极端天气碳排放

Group-wise co-salient object detection via multi-view self-labeling novel class discovery

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Frontiers of Computer Science 2024年第2期18卷 259-261页

作者： Yang WU Gang DONG Lingyan LIANG Yaqian ZHAO Kaihua ZHANG Inspur Electronic Information Industry Co. Ltd.Beijing 100080China jiangsu Key Laboratory of Big Data Analysis technology and jiangsu collaborative innovation center of atmospheric environment and equipment technology Nanjing University of Information Science and TechnologyNanjing 210044China

1 Introduction Co-salient object detection(CoSOD)aims to extract the salient object(s)that are common across a group of relevant images[1].Group-wise clue plays a crucial role in accurately predicting the co-salient regions.Therefore,numerous groupwise deep models have been proposed by exploring consistency across images in unsupervised clustering manners[2-4]or the semantic connections guidance information[5].

关键词： consistency Group semantic

Predominant types of regional cold waves in North China and their historical changes

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atmospheric and Oceanic Science Letters 2024年第4期17卷 46-51页

作者： Xinyi Cheng Yiyi Zhang Jiandong Li Xin Hao center for Climate System Prediction Research/collaborative innovation center on Forecast and Evaluation of Meteorological Disasters/Key Laboratory of Meteorological Disaster Ministry of EducationNanjing University of Information Science&TechnologyNanjingChina Nansen-Zhu International Research Centre Institute of Atmospheric PhysicsChinese Academy of SciencesBeijingChina jiangsu Key Laboratory of atmospheric environment Monitoring and Pollution Control Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment TechnologySchool of Environmental Science and EngineeringNanjing University of Information Science&TechnologyNanjingChina

寒潮事件对东亚地区的社会经济,生态系统和人体健康影响巨大.根据1980-2019年间10月至次年3月的每日寒潮记录和K-means聚类,本文识别出了中国两种不同类型的区域性寒潮(T1和T2).T1区域性寒潮主要影响东北地区,T2区域性寒潮则主要影响华... 详细信息

寒潮事件对东亚地区的社会经济,生态系统和人体健康影响巨大.根据1980-2019年间10月至次年3月的每日寒潮记录和K-means聚类,本文识别出了中国两种不同类型的区域性寒潮(T1和T2).T1区域性寒潮主要影响东北地区,T2区域性寒潮则主要影响华北和东部地区.与T1区域性寒潮相比T2区域性寒潮强度更强,持续时间更长,影响范围更广.1980-2019年期间,T1区域性寒潮的频率显著增加,而T2区域性寒潮的频率则没有趋势变化T1和T2区域性寒潮事件均与西伯利亚高压增强有关,然而与它们相关的对流层中层波列明显不同.在T1区域性寒潮事件发生期间,西伯利亚蒙古上空出现负-正模态的500-hPa位势高度异常波列,削弱了东亚大槽,导致西伯利亚冷空气东移.T1区域寒潮频次增加趋势可能与全球变暖弓|起的500-hPa位势高度的线性趋势变化有关与T2区域寒潮事件相关的波列则在乌拉尔山脉,蒙古和华北地区形成了脊_槽脊环流异常,导致冷空气向东南方向入侵.本文得出结论,由于两类区域寒潮影响不同,西伯利亚高压增强和对流层中层波列模态在我国区域性寒潮事件的预报中应综合考虑.

关键词：寒潮 K-means聚类西伯利亚高压波列

Community-Level Practice Checklists for Health Protection During Cold Spells in China

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China CDC weekly 2024年第5期6卷 83-87页

作者： Jing Shang Mengzhen Zhao Zhao Liu Xiya Zhang Shiguang Miao Ishaq D.Sulaymon Wenjia Cai Institute of Urban Meteorology CMABeijingChina School of Management and Economics Beijing Institute of TechnologyBeijingChina School of Airport Economics and Management Beijing Institute of Economics and ManagementBeijingChina Department of Earth System Science Tsinghua UniversityBeijingChina Sand and Dust Storm Warning Regional center National Center for MeteorologyJeddahSaudi Arabia jiangsu Key Laboratory of atmospheric environment Monitoring and Pollution Control Collaborative Innovation Center of Atmospheric Environment and Equipment TechnologySchool of Environmental Science and EngineeringNanjing University of Information Science and TechnologyNanjing CityJiangsu ProvinceChina

Communities play a crucial role in protecting the health of vulnerable populations such as the elderly,low-income groups,and high-risk individuals during cold spells.However,current strategies for responding to cold spells primarily consist of programmatic policies that lack practicality,specificity,and detailed implementation guidelines for community workers.Therefore,this study aims to identify and analyze the challenges faced by communities in responding to cold spells,review international experiences,and develop a set of practical checklists for community-level health protection.These checklists will assist community workers and volunteers in effectively preparing for,responding to,and recovering from cold spells.

关键词： preparing income primarily

Steganalysis of LSB Matching Using Characteristic Function Moment of Pixel Differences

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China Communications 2016年第7期13卷 66-73页

作者： Xianyi Chen Guangyong Gao Dandan Liu Zhihua Xia jiangsu Engineering center of Network Monitoring Jiangsu Collaborative Innovation Center on Atmospheric Environment and Equipment TechnologySchool of Computer and SoftwareNanjing University of Information Science & Technology School of Information Science & technology Jiujiang University

Nowadays,many steganographic tools have been developed,and secret messages can be imperceptibly transmitted through public networks.This paper concentrates on steganalysis against spatial least significant bit(LSB) matching,which is the prototype of many advanced information hiding methods.Many existing algorithms deal with steganalysis problems by using the dependencies between adjacent pixels.From another aspect,this paper calculates the differences among pixel pairs and proves that the histogram of difference values will be smoothed by stego noises.We calculate the difference histogram characteristic function(DHCF) and deduce that the moment of DHCFs(DHCFM) will be diminished after stego bits are hidden in the image.Accordingly,we compute the DHCFMs as the discriminative features.We calibrate the features by decreasing the influence of image content on them and train support vector machine classifiers based on the calibrated features.Experimental results demonstrate that the DHCFMs calculated with nonadjacent pixels are helpful to detect stego messages hidden by LSB matching.

关键词：特征函数相邻像素矩匹配 LSB 差异分析支持向量机分类器应用秘密信息

SAC-Based Computation Offloading for Reconfigurable Intelligent Surface-Aided Mobile Edge Networks

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China Communications 2024年第6期21卷 261-270页

作者： Li Bin Qian Zhen Fei Zesong School of Computer Science Nanjing University of Information Science&TechnologyNanjing 210044China jiangsu collaborative innovation center of atmospheric environment and equipment technology(CICAEET) Nanjing University of Information Science&TechnologyNanjing 210044 School of Information and Electronics Beijing Institute of TechnologyBeijing 100081China

In this paper,we concentrate on a reconfigurable intelligent surface(RIS)-aided mobile edge computing(MEC)system to improve the offload efficiency with moving user equipments(UEs).We aim to minimize the energy consumption of all UEs by jointly optimizing the discrete phase shift of RIS,UEs’transmitting power,computing resources allocation,and the UEs’task offloading strategies for local computing and offloading.The formulated problem is a sequential decision making across multiple coherent time slots.Furthermore,the mobility of UEs brings uncertainties into the decision-making process.To cope with this challenging problem,the deep reinforcement learning-based Soft Actor-Critic(SAC)algorithm is first proposed to effectively optimize the discrete phase of RIS and the UEs’task offloading strategies.Then,the transmitting power and computing resource allocation can be determined based on the action.Numerical results demonstrate that the proposed algorithm can be trained more stably and perform approximately 14%lower than the deep deterministic policy gradient benchmark in terms of energy consumption.

关键词： MEC RIS soft actor-critic user mobility