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Heterogeneous information phase space reconstruction and stability prediction of filling body–surrounding rock combination

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International Journal of Minerals,Metallurgy and Materials 2024年第7期31卷 1500-1511页

作者： Dapeng Chen Shenghua Yin Weiguo Long Rongfu yan Yufei Zhang Zepeng yan Leiming Wang Wei Chen School of Civil and Resources Engineering University of Science and Technology of BeijingBeijing 100083China Production Technology Department Longshou MineJinchuan Group Co.Ltd.Jinchang 737100China School of Civil Engineering and Architecture East China Jiaotong UniversityNanchang 330013China

Traditional research believes that the filling body can effectively control stress concentration while ignoring the problems of unknown stability and the complex and changeable stress distribution of the filling body–surrounding rock combination under high-stress *** monitoring data processing methods cannot fully consider the complexity of monitoring objects,the diversity of monitoring methods,and the dynamics of monitoring *** solve this problem,this paper proposes a phase space reconstruction and stability prediction method to process heterogeneous information of backfill–surrounding rock *** three-dimensional monitoring system of a large-area filling body–surrounding rock combination in Longshou Mine was constructed by using drilling stress,multipoint displacement meter,and *** information,such as the stress and displacement of the filling body–surrounding rock combination,was continuously *** with the average mutual information method and the false nearest neighbor point method,the phase space of the heterogeneous information of the filling body–surrounding rock combination was then *** this paper,the distance between the phase point and its nearest point was used as the index evaluation distance to evaluate the stability of the filling body–surrounding rock *** evaluated distances(ED)revealed a high sensitivity to the stability of the filling body–surrounding rock *** new method was then applied to calculate the time series of historically ED for 12 measuring points located at Longshou *** moments of mutation in these time series were at least 3 months ahead of the roadway return *** the ED prediction experiments,the autoregressive integrated moving average model showed a higher prediction accuracy than the deep learning models(long short-term memory and Transformer).Furthermore,the root-mean-square error distribution of the prediction results peaked at 0

关键词： deep mining filling body–surrounding rock combination phase space reconstruction multiple time series stability prediction

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High-Order Decoupled and Bound Preserving Local Discontinuous Galerkin Methods for a Class of Chemotaxis Models

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Communications on Applied Mathematics and Computation 2024年第1期6卷 372-398页

作者： Wei Zheng yan Xu School of Mathematical Sciences University of Science and Technology of ChinaHefei230026AnhuiChina

In this paper,we explore bound preserving and high-order accurate local discontinuous Galerkin(LDG)schemes to solve a class of chemotaxis models,including the classical Keller-Segel(KS)model and two other density-dependent *** use the convex splitting method,the variant energy quadratization method,and the scalar auxiliary variable method coupled with the LDG method to construct first-order temporal accurate schemes based on the gradient flow structure of the *** semi-implicit schemes are decoupled,energy stable,and can be extended to high accuracy schemes using the semi-implicit spectral deferred correction *** bound preserving DG discretizations are only worked on explicit time integration methods and are difficult to get high-order *** overcome these difficulties,we use the Lagrange multipliers to enforce the implicit or semi-implicit LDG schemes to satisfy the bound constraints at each time *** bound preserving limiter results in the Karush-Kuhn-Tucker condition,which can be solved by an efficient active set semi-smooth Newton *** numerical experiments illustrate the high-order accuracy and the effect of bound preserving.

关键词： Chemotaxis models Local discontinuous Galerkin(LDG)scheme Convex splitting method Variant energy quadratization method Scalar auxiliary variable method Spectral deferred correction method

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Research on casing deformation prevention technology based on cementing slurry system optimization

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Petroleum Science 2024年第2期21卷 1231-1240页

作者： yan yan Meng Cai Wen-Hai Ma Xiao-Chuan Zhang Li-Hong Han Yong-Hong Liu State Key Laboratory for Performance and Structure Safety of Petroleum Tubular Goods and Equipment Materials CNPC Tubular Goods Research InstituteXi©an710077ShaanxiChina College of Mechanical and Electrical Engineering China University of Petroleum(East China)Qingdao266580ShandongChina Shale Gas Evaluation and Exploitation Key Laboratory of Sichuan Province Chengdu610095SichuanChina CNPC Daqing Oilfield Company Daqing163453HeilongjiangChina

The casing deformation prevention technology based on the optimization of cement slurry is proposed to reduce the casing deformation of shale oil and gas wells during hydraulic fracturing. In this paper, the fracture mechanism of hollow particles in cement sheath was firstly analyzed by discrete element method, and the effect of hollow particles in cement on casing deformation was investigated by laboratory experiment method. Finally, field test was carried out to verify the improvement effect of the casing deformation based on cement slurry modification. The results show that the formation displacement can be absorbed effectively by hollow particles inside the cement transferring the excessive deformation away from casing. The particles in the uncemented state provide deformation space during formation slipping. The casing with diameter of 139.7 mm could be passed through by bridge plug with the diameter of 99 mm when the mass ratio of particle/cement reaches 1:4. According to the field test feedback, the method based on optimization of cement slurry can effectively reduce the risk of casing deformation, and the recommended range of hollow microbeads content in the cement slurry is between 15% and 25%.

关键词： Cement slurry Hollow ceramsite Casing deformation Formation slip Field test

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Real-time model correction using Kalman filter for Raman-controlled cell culture processes

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Chinese Journal of Chemical Engineering 2024年第6期70卷 251-260页

作者： Xiaoxiao Dong Zhuohong He Xu yan Dong Gao Jingyu Jiao yan Sun Haibin Wang Haibin Qu Pharmaceutical Informatics Institute College of Pharmaceutical SciencesZhejiang UniversityHangzhou 310058China Hisun Biopharmaceutical Co.Ltd. Hangzhou 311404China

Raman spectroscopy has found extensive use in monitoring and controlling cell culture *** this context,the prediction accuracy of Raman-based models is of paramount ***,models established with data from manually fed-batch cultures often exhibit poor performance in Raman-controlled ***,there is a need for effective methods to rectify these *** objective of this paper is to investigate the efficacy of Kalman filter(KF)algorithm in correcting Raman-based models during cell ***,partial least squares(PLS)models for different components were constructed using data from manually fed-batch cultures,and the predictive performance of these models was ***,various correction methods including the PLS-KF-KF method proposed in this study were employed to refine the PLS ***,a case study involving the auto-control of glucose concentration demonstrated the application of optimal model correction *** results indicated that the original PLS models exhibited differential performance between manually fed-batch cultures and Raman-controlled *** glucose,the root mean square error of prediction(RMSEP)of manually fed-batch culture and Raman-controlled culture was 0.23 and 0.40 g·L^(-1).With the implementation of model correction methods,there was a significant improvement in model performance within Raman-controlled *** RMSEP for glucose from updating-PLS,KF-PLS,and PLS-KF-KF was 0.38,0.36 and 0.17 g·L^(-1),***,the proposed PLS-KF-KF model correction method was found to be more effective and stable,playing a vital role in the automated nutrient feeding of cell cultures.

关键词： Raman spectroscopy Model correction Algorithm Model-predictive control Bioprocess

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High-temperature dielectric polymer composite for high power energy storage applications

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Science China Chemistry 2024年第8期67卷 2425-2426页

作者： Xiangyan Yu Haixue yan School of Engineering and Materials Science Queen Mary University of LondonLondon E14NSUK

Polymer-based dielectric films are the main component of dielectric capacitors due to their high power density, which plays an important role in power electrical systems using renewable energy, such as electric vehicles, solar panel, wind power [1]. However, the energy density of dielectrics is lower than that of other energy storage materials, such as batteries or supercapacitors. High energy density of the dielectric is related to high dielectric permittivity and high dielectric breakdown strength (DBS).

关键词： composite dielectric energy

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The impact of water quality on the formation of halogenated benzoquinones and the adsorption efficiency by activated carbon

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Journal of Environmental Sciences 2024年第1期135卷 693-702页

作者： Yongjing Wang Song Gao Xinyu yan Songtao Wang Ruolin Zhang yan Zhou Lianhai Ren Cheng Li State Environmental Protection Key Laboratory of Food Chain Pollution Control Beijing Technology and Business UniversityBeijing 100048China Institute of Scientific and Technical Information of China Beijing 100038China Institute of Quality Standard and Testing Technology Beijing Academy of Agriculture and Forestry SciencesBeijing 100097China Key Laboratory of Cleaner Production and Integrated Resource Utilization of China National Light Industry Beijing Technology and Business UniversityBeijing 100048China

Halogenated benzoquinones(HBQs)could cause bladder cancer,but there were few related studies on the generation and *** this study,the impact of different precursors,pH,bromide concentration,and algae-derived organic matters on the formation of HBQs and the removal efficiency by activated carbon were *** was found that the chlorination of bisphenol A produced the most 2,6-dichloro-1,4-benzoquinone(2,6-DCBQ),reaching 14.86μg/L at 1 hr,followed by tyrosine,2-chlorophenol,P-hydroxybenzoic acid,trichlorophenol,and *** production of 2,6-DCBQ increased first and then decreased from 0 to 36 hr(chlorination doses 0-20 mg/L),indicating that HBQs were unstable in ***(THMs)were detected during chlorination,and the concentration increased with prolongation of reaction time.2,6-DCBQ production decreased and 2,6-dibromo-1,4-benzoquinone(2,6-DBBQ)production increased with increment bromide concentration and the bromide promoted the formation of *** production of 2,6-DCBQ decreased with increase of pH,and the maximum production was 141.38μg/L at pH of *** aeruginosa,Chlorella algae cells,and intracellular organic matters(IOM)could be chlorinated as potential precursors for *** most amount of 2,6-DCBQ was generated from algae cells of Microcystis aeruginosa,followed by Chlorella algae cells,Microcystis aeruginosa IOM,and Chlorella *** study compared the removal efficiency of HBQs by granular activated carbon(GAC)and columnar activated carbon(CAC)under different carbon doses and initial concentrations of *** was found that the removal efficiency by GAC(80.1%)was higher than that by CAC(51.8%),indicating that GAC has better control for HBQs.

关键词： HBQS DBPS Drinking water Algae derived organic matters Activated carbon

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Multi-Scale Feature Fusion Model for Bridge Appearance Defect Detection

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Big Data Mining and Analytics 2024年第1期7卷 1-11页

作者： Rong Pang yan yang Aiguo Huang yan Liu Peng Zhang Guangwu Tang School of Computing and Artificial Intelligence Southwest Jiaotong UniversityChengdu 611756China China Merchants Chongqing Road Engineering Inspection Center Co. Ltd.Chongqing 400067China State Key Laboratory of Bridge Engineering Structural Dynamics Chongqing 400067China

Although the Faster Region-based Convolutional Neural Network(Faster R-CNN)model has obvious advantages in defect recognition,it still cannot overcome challenging problems,such as time-consuming,small targets,irregular shapes,and strong noise interference in bridge defect *** deal with these issues,this paper proposes a novel Multi-scale Feature Fusion(MFF)model for bridge appearance disease ***,the Faster R-CNN model adopts Region Of Interest(ROl)pooling,which omits the edge information of the target area,resulting in some missed detections and inaccuracies in both detecting and localizing bridge ***,this paper proposes an MFF based on regional feature Aggregation(MFF-A),which reduces the missed detection rate of bridge defect detection and improves the positioning accuracy of the target ***,the Faster R-CNN model is insensitive to small targets,irregular shapes,and strong noises in bridge defect detection,which results in a long training time and low recognition ***,a novel Lightweight MFF(namely MFF-L)model for bridge appearance defect detection using a lightweight network EfficientNetV2 and a feature pyramid network is proposed,which fuses multi-scale features to shorten the training speed and improve recognition ***,the effectiveness of the proposed method is evaluated on the bridge disease dataset and public computational fluid dynamic dataset.

关键词： defect detection Multi-scale Feature Fusion(MFF) Region Of Interest(ROl)alignment lightweight network

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Lipid nanovehicles overcome barriers to systemic RNA delivery: Lipid components, fabrication methods, and rational design

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Acta Pharmaceutica Sinica B 2024年第2期14卷 579-601页

作者： Jing yan Hao Zhang Guangfeng Li Jiacan Su yan Wei Can Xu Institute of Translational Medicine Shanghai UniversityShanghai 200444China Institute of Medicine Shanghai UniversityShanghai 200444China Department of Orthopedics Xinhua HospitalShanghai Jiao Tong University School of MedicineShanghai 200092China Department of Orthopedics Shanghai Zhongye HospitalShanghai 200941China Organoid Research Center Shanghai UniversityShanghai 200444China Department of Gastroenterology Changhai HospitalShanghai 200433China

Lipid nanovehicles are currently the most advanced vehicles used for RNA delivery,as demonstrated by the approval of patisiran for amyloidosis therapy in *** illuminate the unique superiority of lipid nanovehicles in RNA delivery,in this review,we first introduce various RNA therapeutics,describe systemic delivery barriers,and explain the lipid components and methods used for lipid nanovehicle ***,we emphasize crucial advances in lipid nanovehicle design for overcoming barriers to systemic RNA ***,the current status and challenges of lipid nanovehicle-based RNA therapeutics in clinical applications are also *** objective is to provide a comprehensive overview showing how to utilize lipid nanovehicles to overcome multiple barriers to systemic RNA delivery,inspiring the development of more high-performance RNA lipid nanovesicles in the future.

关键词： Lipid nanovehicles RNAtherapeutics Barriers to systemicRNA delivery Lipid components Fabricationmethods Lipid nanovehicledesign Extrahepatictissue targeting Organ tropism

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ON THE STABILITY OF PERIODIC SOLUTIONS OF PIECEWISE SMOOTH PERIODIC DIFFERENTIAL EQUATIONS

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Acta Mathematica Scientia 2024年第4期44卷 1524-1535页

作者： Maoan HAN yan YE School of Mathematical Sciences Zhejiang Normal UniversityJinhua 321000China

In this paper,we address the stability of periodic solutions of piecewise smooth periodic differential *** studying the Poincarémap,we give a sufficient condition to judge the stability of a periodic *** also present... 详细信息

关键词： periodic solution Poincarémap periodic equation stability

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Model architecture level privacy leakage in neural networks

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Science China(Information Sciences) 2024年第3期67卷 20-32页

作者： yan LI Hongyang yan Teng HUANG Zijie PAN Jiewei LAI Xiaoxue ZHANG Kongyang CHEN Jin LI Institute of Artificial Intelligent and Blockchain Guangzhou University Pazhou Lab

Privacy leakage is one of the most critical issues in machine learning and has attracted growing interest for tasks such as demonstrating potential threats in model attacks and creating model *** recent years, numerous studies have revealed various privacy leakage risks(e.g., data reconstruction attack, membership inference attack, backdoor attack, and adversarial attack) and several targeted defense approaches(e.g., data denoising, differential privacy, and data encryption). However, existing solutions generally focus on model parameter levels to disclose(or repair) privacy threats during the model training and/or model interference process, which are rarely applied at the model architecture level. Thus, in this paper, we aim to exploit the potential privacy leakage at the model architecture level through a pioneer study on neural architecture search(NAS) paradigms which serves as a powerful tool to automate a neural network *** investigating the NAS procedure, we discover two attack threats in the model architecture level called the architectural dataset reconstruction attack and the architectural membership inference attack. Our theoretical analysis and experimental evaluation reveal that an attacker may leverage the output architecture of an ongoing NAS paradigm to reconstruct its original training set, or accurately infer the memberships of its training set simply from the model architecture. In this work, we also propose several defense approaches related to these model architecture attacks. We hope our work can highlight the need for greater attention to privacy protection in model architecture levels(e.g., NAS paradigms).

关键词： neural architecture search data reconstruction attack membership inference attack

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