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Flume Experiment Investigation on Propagation Characteristics of Tidal Bore in A Curved Channel

China Ocean Engineering 2023年第1期37卷 131-144页

作者： FAN Jun TAO Ai-feng shi mo-quan LI Ying PENG Ji Key Laboratory of Ministry of Education for Coastal Disaster and Protection Hohai UniversityNanjing 210098China College of Harbour Coastal and Offshore EngineeringHohai UniversityNanjing 210098China The Adminstrative Committee of Nantong Haimen Sanchang Industrial Park Nantong 226121China Zhejiang University of Water Resources and Electric Power Hangzhou 310018China China Renewable Energy Engineering Institute Beijing 100120China

Tidal bore is a special and intensive form of flow movement induced by tidal effect in estuary areas, which has complex characteristics of profile, propagation and flow velocity. Although it has been widely studied for the generation mechanism, propagation features and influencing factors, the curved channel will complicate the characteristics of tidal bore propagation, which need further investigation compared with straight channel. In this study, the flume experiments for both undular and breaking bores’ propagation in curved channel are performed to measure the freesurface elevation and flow velocity by ultrasonic sensors and ADV respectively. The propagation characteristics,including tidal bore height, cross-section surface gradient, tidal bore propagation celerity, and flow velocity are obtained for both sides of the curved channel. And three bore intensities are set for each type of tidal bores. The freesurface gradients are consistently enlarged in high-curvature section for undular and breaking bores, but have distinct behaviors in low-curvature section. The spatial distributions of tidal bore propagation celerity and flow velocity are compared between concave and convex banks. This work will provide experimental reference for engineering design of beach and seawall protection, erosion reduction and siltation promotion in estuary areas with the existence of tidal bores.

关键词： tidal bore curved channel flume experiment propagation celerity bore intensity

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Regulation and function of endoplasmic reticulum autophagy in neurodegenerative diseases

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Neural Regeneration Research 2025年第1期20卷 6-20页

作者： Xiu-Yun Zhao De-En Xu Ming-Lei Wu Ji-Chuan Liu Zi-Ling shi quan-Hong Ma Department of Neurology and Clinical Research Center of Neurological Disease the Second Affiliated Hospital of Soochow UniversitySuzhouJiangsu ProvinceChina Institute of Neuroscience&Jiangsu Key Laboratory of Translational Research and Therapy for Neuro-Psycho-Diseases Soochow UniversitySuzhouJiangsu ProvinceChina Department of Neurology Jiangnan University Medical CenterWuxiJiangsu ProvinceChina

The endoplasmic reticulum,a key cellular organelle,regulates a wide variety of cellular *** reticulum autophagy,one of the quality control systems of the endoplasmic reticulum,plays a pivotal role in maintaining endoplasmic reticulum homeostasis by controlling endoplasmic reticulum turnover,remodeling,and *** this review,we briefly describe the endoplasmic reticulum quality control system,and subsequently focus on the role of endoplasmic reticulum autophagy,emphasizing the spatial and temporal mechanisms underlying the regulation of endoplasmic reticulum autophagy according to cellular *** also summarize the evidence relating to how defective or abnormal endoplasmic reticulum autophagy contributes to the pathogenesis of neurodegenerative *** summary,this review highlights the mechanisms associated with the regulation of endoplasmic reticulum autophagy and how they influence the pathophysiology of degenerative nerve *** review would help researchers to understand the roles and regulatory mechanisms of endoplasmic reticulum-phagy in neurodegenerative disorders.

关键词： autophagy endoplasmic reticulum endoplasmic reticulum autophagy endoplasmic reticulum quality control system endoplasmic reticulum receptors endoplasmic reticulum-associated degradation neurodegeneration neurodegenerative disease selective autophagy unfolded protein response

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基于区块链的车联网跨域数据安全传输系统设计

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现代电子技术 2025年第01期48卷 71-79页

作者：陈晨王斓凯施佺南通大学信息化中心南通大学交通与土木工程学院

为有效应对车联网系统在数据传输过程中的安全问题，提出一种基于区块链的车联网跨域数据安全传输系统。该系统将车联网安全数据传输过程划分为注册、安全通信与数据共享三个关键环节。在注册阶段，车辆和路边单元需要通过可信机构完成... 详细信息

为有效应对车联网系统在数据传输过程中的安全问题，提出一种基于区块链的车联网跨域数据安全传输系统。该系统将车联网安全数据传输过程划分为注册、安全通信与数据共享三个关键环节。在注册阶段，车辆和路边单元需要通过可信机构完成注册，以确保其的身份合法性；在通信阶段，为了减少路边单元与车辆频繁认证，设计了跨域认证的方法，保障数据传输的可靠性和完整性，并引入假名来保护用户隐私；在共享阶段，文中设计了基于多线程遍历共享广播森林的事务广播算法，利用广度优先搜索思想建立广播森林，并使用多线程遍历进行数据事务广播传输。实验仿真结果显示，文中方案的签名计算成本减少70%，验证计算成本减少41%；其次，在ER模型下，相比使用Gossip协议进行事务数据传输，该方案中交通数据事务总时间降低了93%；在BA模型下降低了87%。

关键词：区块链车联网身份认证密钥协商广播森林数据安全传输系统

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Progress on spatial prediction methods for soil particle-size fractions

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Journal of Geographical Sciences 2023年第7期33卷 1553-1566页

作者： shi Wenjiao ZHANG mo Key Laboratory of Land Surface Pattern and Simulation of CAS Institute of Geographic Sciences and Natural Resources ResearchCASBeijing 100101China State Key Laboratory of Resources and Environmental Information System Institute of Geographic Sciences and Natural Resources ResearchCASBeijing 100101China College of Resources and Environment University of Chinese Academy of SciencesBeijing 100049China

Soil particle-size fractions(PSFs),including three components of sand,silt,and clay,are very improtant for the simulation of land-surface process and the evaluation of ecosystem *** spatial prediction of soil PSFs can help better understand the simulation processes of these *** soil PSFs are compositional data,there are some special demands such as the constant sum(1 or 100%) in the interpolation *** addition,the performance of spatial prediction methods can mostly affect the accuracy of the spatial ***,we proposed a framework for the spatial prediction of soil *** included log-ratio transformation methods of soil PSFs(additive log-ratio,centered log-ratio,symmetry log-ratio,and isometric log-ratio methods),interpolation methods(geostatistical methods,regression models,and machine learning models),validation methods(probability sampling,data splitting,and cross-validation) and indices of accuracy assessments in soil PSF interpolation and soil texture classification(rank correlation coefficient,mean error,root mean square error,mean absolute error,coefficient of determination,Aitchison distance,standardized residual sum of squares,overall accuracy,Kappa coefficient,and Precision-Recall curve) and uncertainty analysis indices(prediction and confidence intervals,standard deviation,and confusion index).moreover,we summarized several paths on improving the accuracy of soil PSF interpolation,such as improving data distribution through effective data transformation,choosing appropriate prediction methods according to the data distribution,combining auxiliary variables to improve mapping accuracy and distribution rationality,improving interpolation accuracy using hybrid models,and developing multi-component joint *** the future,we should pay more attention to the principles and mechanisms of data transformation,joint simulation models and high accuracy surface modeling methods for multi-components,as well as the combi

关键词： soil interpolation spatial accuracy geostatistics machine learning high accuracy surface modeling

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Key issues and progress of industrial big data-based intelligent blast furnace ironmaking technology

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International Journal of Minerals,Metallurgy and Materials 2023年第9期30卷 1651-1666页

作者： quan shi Jue Tang Mansheng Chu School of Metallurgy Northeastern UniversityShenyang 110819China Institute for Frontier Technologies of Low-carbon Steelmaking Northeastern UniversityShenyang 110819China Engineering Research Center of Frontier Technologies for Low-carbon Steelmaking(Ministry of Education) Shenyang 110819China

Blast furnace (BF) ironmaking is the most typical “black box” process, and its complexity and uncertainty bring forth great challenges for furnace condition judgment and BF operation. Rich data resources for BF ironmaking are available, and the rapid development of data science and intelligent technology will provide an effective means to solve the uncertainty problem in the BF ironmaking process. This work focused on the application of artificial intelligence technology in BF ironmaking. The current intelligent BF ironmaking technology was summarized and analyzed from five aspects. These aspects include BF data management, the analyses of time delay and correlation, the prediction of BF key variables, the evaluation of BF status, and the multi-objective intelligent optimization of BF operations. Solutions and suggestions were offered for the problems in the current progress, and some outlooks for future prospects and technological breakthroughs were added. To effectively improve the BF data quality, we comprehensively considered the data problems and the characteristics of algorithms and selected the data processing method scientifically. For analyzing important BF characteristics, the effect of the delay was eliminated to ensure an accurate logical relationship between the BF parameters and economic indicators. As for BF parameter prediction and BF status evaluation,a BF intelligence model that integrates data information and process mechanism was built to effectively achieve the accurate prediction of BF key indexes and the scientific evaluation of BF status. During the optimization of BF parameters, low risk, low cost, and high return were used as the optimization criteria, and while pursuing the optimization effect, the feasibility and site operation cost were considered *** work will help increase the process operator’s overall awareness and understanding of intelligent BF technology. Additionally, combining big data technology with the proces

关键词： BF ironmaking intelligent BF industrial big data machine learning integrated mechanism and data

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Process metallurgy and data-driven prediction and feedback of blast furnace heat indicators

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International Journal of Minerals,Metallurgy and Materials 2024年第6期31卷 1228-1240页

The prediction and control of furnace heat indicators are of great importance for improving the heat levels and conditions of the complex and difficult-to-operate hour-class delay blast furnace(BF)*** this work,a prediction and feedback model of furnace heat indicators based on the fusion of data-driven and BF ironmaking processes was *** data on raw and fuel materials,process op-eration,smelting state,and slag and iron discharge during the whole BF process comprised 171 variables with 9223 groups of data and were comprehensively analyzed.A novel method for the delay analysis of furnace heat indicators was *** extracted delay variables were found to play an important role in *** method that combined the genetic algorithm and stacking efficiently im-proved performance compared with the traditional machine learning algorithm in improving the hit ratio of the furnace heat prediction *** hit ratio for predicting the temperature of hot metal in the error range of±10℃ was 92.4%,and that for the chemical heat of hot metal in the error range of±0.1wt%was 93.3%.On the basis of the furnace heat prediction model and expert experience,a feedback model of furnace heat operation was established to obtain quantitative operation suggestions for stabilizing BF heat *** sugges-tions were highly accepted by BF ***,the comprehensive and dynamic model proposed in this work was successfully ap-plied in a practical BF *** improved the BF temperature level remarkably,increasing the furnace temperature stability rate from 54.9%to 84.9%.This improvement achieved considerable economic benefits.

关键词： blast furnace furnace heat genetic algorithm stacking prediction and feedback

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Effect of Na^+ impregnated activated carbon on the adsorption of NH_4^+-N from aqueous solution

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Journal of Environmental Sciences 2013年第8期25卷 1501-1510页

作者： mo shi Zhengfang Wang Zheng Zheng Environmental Science and Engineering Department Fudan University

Two kinds of activated carbons modified by Na＋ impregnation after pre-treatments involving oxidation by nitric acid or acidification by hydrochloric acid （denoted as AC/N-Na and AC/HCl-Na, respectively）, were used as adsorbents to remove NH4＋-N. The surface features of samples were investigated by BET, SEM, XRD and FT-IR. The adsorption experiments were conducted in equilibrium and kinetic conditions. Influencing factors such as initial solution pH and initial concentration were investigated. A possible mechanism was proposed. Results showed that optimal NH4＋-N removal efficiency was achieved at a neutral pH condition for the modified ACs. The Langmuir isotherm adsorption equation provided a better fit than other models for the equilibrium study. The adsorption kinetics followed both the pseudo second-order kinetics model and intra-particle kinetic model. Chemical surface analysis indicated that Na＋ ions form ionic bonds with available surface functional groups created by pre-treatment, especially oxidation by nitric acid, thus increasing the removal efficiency of the modified ACs for NH4＋-N. Na＋-impregnated ACs had a higher removal capability in removing NH4＋-N than unmodified AC, possibly resulting from higher numbers of surface functional groups and better intra-particle diffusion. The good fit of Langmuir isotherm adsorption to the data indicated the presence of monolayer NH4＋-N adsorption on the active homogenous sites within the adsorbents. The applicability of pseudo second-order and intra-particle kinetic models revealed the complex nature of the adsorption mechanism. The intra-particle diffusion model revealed that the adsorption process consisted not only of surface adsorption but also intra-particle diffusion.

关键词： NH4+-N adsorption Na+-impregnated activated carbon isotherm kinetics mechanism

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Visual interpretability for deep learning：a survey

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Frontiers of Information Technology & Electronic Engineering 2018年第1期19卷 27-39页

作者： quan-shi ZHANG Song-chun ZHU University of California Los Angeles California 90095 USA

This paper reviews recent studies in understanding neural-network representations and learning neural networks with interpretable/disentangled middle-layer *** deep neural networks have exhibited superior performance in various tasks,interpretability is always Achilles' heel of deep neural *** present,deep neural networks obtain high discrimination power at the cost of a low interpretability of their black-box *** believe that high model interpretability may help people break several bottlenecks of deep learning,e.g.,learning from a few annotations,learning via human–computer communications at the semantic level,and semantically debugging network *** focus on convolutional neural networks(CNNs),and revisit the visualization of CNN representations,methods of diagnosing representations of pre-trained CNNs,approaches for disentangling pre-trained CNN representations,learning of CNNs with disentangled representations,and middle-to-end learning based on model ***,we discuss prospective trends in explainable artificial intelligence.

关键词： Artificial intelligence Deep learning Interpretable model

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Oriented Antibody Immobilization and Immunoassay Based on Boronic Acid-containing Polymer Brush

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Chinese Journal of Polymer Science 2018年第4期36卷 472-478页

作者： Jie Zhao Ru mo Li-Mei Tian Ling-Jie Song shi-Fang Luan Jing-Hua Yin Lu-quan Ren Key Laboratory of Bionic Engineering Ministry ofEdueationJilin UniversityChangchun 130022China State Key Laboratory of Polymer Physics and Chemistry Changchun Institute of Applied ChemistryChinese Academy of SciencesChangchun 130022China Jilin Province People's Hospital Changchun 130021China

High sensitive immunoassay platforms have gained intense attention due to their vital roles in early-stage disease diagnosis and therapeutic information feedback. Although random covalent-binding of antibody has been widely adopted in immunoassays due to its simplicity and effectiveness, it readily loses its activity and fails to exhibit high antigen-binding capacity. In this work, copolymer of zwitterionic sulfobetaine methacrylate（SBMA） and glycidyl methacrylate（GMA） brushes were immobilized onto inert polypropylene（PP） via surface-initiated atom transfer radical polymerization（ATRP） based on biomimetic dopamine pretreatment. Subsequently, boronic acid（BA） groups were covalently bonded via active GMA units, followed by the introduction of oriented immobilization of antibody. Owing to the oriented immobilization of antibody facilitated by BA groups in polymer brush, the bioactivity of antibody is well preserved, which endows the surface with significantly enhanced antigen-binding capacity. moreover, the existence of SBMA segments in polymer brushes renders the surface high resistance to nonspecific protein adsorption, significantly alleviating the signal interference of antigen recognition. This strategy could find potential applications in developing high sensitive immunoassay platforms based on the different substrates.

关键词： Biomimetic dopamine Atom transfer radical polymerization (ATRP) Boronic acid (BA) Immunoassay Biomimetic

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HIGHLY SENSITIVE CATALASE ELECTRODE BASED ON POLYPYRROLE FILMS WITH MICROCONTAINERS

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Chinese Journal of Polymer Science 2006年第6期24卷 579-584页

作者： Yu-ying Gao Gao-quan shi Department of Chemistry Tsinghua University Beijing 100084 China

Highly sensitive catalase electrodes for sensing hydrogen peroxide have been fabricated based on polypyrrole films with microcontainers. The microcontainers have a cup-like morphology and are arranged in a density of 4000 units cm^-2. Catalase was immobilized into the polypyrrole films with microcontainers （Ppy-mc）, which were coated on a Pt substrate electrode. The catalase/Ppy-mc/Pt electrode showed linear response to hydrogen peroxide in the range of 0-18 mmol/L at a potential of-0.3 V （versus SCE）. Its sensitivity was measured to be approximately 3.64 μA （mmol/L） ^-1 cm^- 2, which is about two times that of the electrode fabricated from a flat Ppy film （catalase/Ppy-flat/Pt electrode）. The electrode is highly selective for hydrogen peroxide and its sensitivity is interfered by potential interferents such as ascorbic acid, urea and fructose. Furthermore, such catalase electrodes showed long-term storage stability of 15 days under dry conditions at 4℃.

关键词： Microstructured polypyrrole Catalase Electropolymerization Sensors Hydrogen peroxide.

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