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HKUST-1 derived one-dimensional Cu/N-doped carbon nanofibers for simultaneous detection of acetaminophen and sulfanilamide

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Progress in Natural science:Materials International 2023年第6期33卷 825-832页

作者： Saisai Chen Chaohai Wang Dayong Xu Jiansheng Li School of Chemical and Environmental Engineering Anhui Polytechnic University Jiangsu Key Laboratory of Chemical Pollution Control and Resources Reuse School of Environmental and Biological Engineering Nanjing University of Science and Technology Henan Key Laboratory of Water Pollution Control and Rehabilitation Technology School of Municipal and Environmental Engineering Henan University of Urban Construction

The design of novel signal amplification elements was key to improving the sensing and analysis performance of electrochemical sensors. In this work, porous one-dimensional copper nitrogen-doped carbon nanofibers(CuNCNFs) were successfully prepared via the coupled process of electrospinning technology and high-temperature pyrolysis. This coupling of multiple processes and the introduction of heteroatoms pyrolyzed the HKUST-1 particles to generate three-dimensional Cu-doped carbon octahedra and mosaic them inside the one-dimensional carbon nitride channels, obtaining small-sized Cu particles while introducing a large number of N species, and constructing a three-dimensional MOFs-derived metal-carbon hybrid one-dimensional multistage carbon nitride structure. The resulting Cu-NCNFs sensor could simultaneously determine acetaminophen and sulfanilamide and exhibit superior electroanalytical performance, reproducibility, stability, and selectivity. This strategy provides a new approach to preparing novel signal amplification elements for the efficient monitoring of micropollutants.

关键词： HKUST-1 Cu/N-doped carbon nanofibers Acetaminophen Sulfanilamide

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Effects of dimethyl ether and ethanol additions on soot transition in ethylene counterflow diffusion flames

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science China(Technological sciences) 2024年第4期67卷 1094-1112页

作者： GUO LinGe YING YaoYao CHEN Chen ZHAO Xuan LIU Dong MIIT Key Laboratory of Thermal Control of Electronic Equipment School of Energy and Power EngineeringNanjing University of Science and TechnologyNanjing 210094China Advanced Combustion Laboratory School of Energy and Power EngineeringNanjing University of Science and TechnologyNanjing 210094China

This paper investigates the effect of blending dimethyl ether(DME)and ethanol on the soot transition periods in ethylene counterflow diffusion flames by using a novel optical diagnostic *** soot critical transition point in different conditions is identified experimentally and *** kinds of flames are carried out to gain the soot critical transition point in counterflow diffusion flames by changing oxygen fraction(Xo)and changing volume flow rates of fuel and oxidizer(Qv).The red-green-blue(RGB)ratio method is used to precisely identify the soot critical transition point,and chemical kinetic simulations are performed to analyze the detailed reaction *** results show that compared to the ethylene flame,the soot critical transition point occurs at a higher Xoand a lower Qvwhen DME or ethanol is *** addition of DME and ethanol can inhibit soot formation,due to the degree of soot formation reaction being lower than the degree of the oxidation reaction in the blending flames.

关键词： optical diagnosis sooting tendency counterflow diffusion flame dimethyl ether ethanol

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Two-Way Neural Network Performance PredictionModel Based onKnowledge Evolution and Individual Similarity

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Computer Modeling in engineering & sciences 2024年第2期138卷 1183-1206页

作者： Xinzheng Wang Bing Guo Yan Shen College of Computer Science Sichuan UniversityChengdu610065China School of Information Science and Engineering Guilin University of TechnologyGuilin541004China School of Control Engineering Chengdu University of Information TechnologyChengdu610225China

Predicting students’academic achievements is an essential issue in education,which can benefit many stakeholders,for instance,students,teachers,managers,*** with online courses such asMOOCs,students’academicrelateddata in the face-to-face physical teaching environment is usually sparsity,and the sample size is *** makes building models to predict students’performance accurately in such an environment even *** paper proposes a Two-WayNeuralNetwork(TWNN)model based on the bidirectional recurrentneural network and graph neural network to predict students’next semester’s course performance using only theirprevious course *** experiments on a real dataset show that our model performs better thanthe baselines in many indicators.

关键词： Computer education performance prediction deep learning

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Sensitivity analysis of modeling parameters to soot and PAHs prediction in ethylene inverse diffusion flame

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science China(Technological sciences) 2024年第2期67卷 486-498页

作者： WU BingKun LI TianJiao LIU Dong MIIT Key Laboratory of Thermal Control of Electronic Equipment School of Energy and Power EngineeringNanjing University of Science and TechnologyNanjing 210094China Advanced Combustion Laboratory School of Energy and Power EngineeringNanjing University of Science and Technology Nanjing 210094China

The soot formation model based on inverse ethylene diffusion flames was performed to study the sensitivity of the soot formation process to the prediction *** effects of efficiency parameters such as soot inception,surface growth and coagulation on the simulation results were studied by using the adjustable efficiency *** addition,the reversible soot model and conjugate heat transfer(CHT)model were also introduced to explore their *** indicated that,among adjustable efficiency parameters,the nucleation efficiency had the greatest influence on the predicted soot and PAHs distributions,while the Habstraction-C2H2-addition(HACA)process and PAH adsorption surface growth efficiencies impacted *** adjustable efficiency parameters had a significant effect on the concentration of soot gaseous precursors and soot particles,but their effects on temperature,gas phase molecules,and intermediate species were not *** the nucleation efficiency increased from 2×10^(-6)to 1×10^(-4),the predicted value of the integrated soot was increased by nearly 50%,and the maximum primary particle number density and the number of aggregates were increased by an order of *** maximum concentration of BAPYR was ***,the peak temperature along the axial direction increased by only 3.5 *** the reversible soot model,the approximation results of the adjustable efficiency parameters could be modified,which showed the feasibility of the *** use of the CHT model promoted pyrolysis of the fuel below the outlet of the fuel tube,with high-temperature zones,soot zones,and PAHs zones moving towards higher flame ***,when using the reversible model and the CHT model,the maximum soot volume fraction decreased by 39%compared with the basic efficiency parameters,while the concentration of BAPYR increased by 162%,and the concentrations of gas phase species were decreased.

关键词： inverse diffusion flames soot formation soot model ethylene

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Strong Structural controllability Based on Leader-Follower Framework

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Journal of Systems science & Complexity 2023年第4期36卷 1498-1518页

作者： QI Wei JI Zhijian LIU Yungang LIN Chong Insitute of Complexity Science College of AutomationQingdao UniversityQingdao 266071China Shandong Key Laboratory of Industrial Control Technology Qingdao UniversityQingdao 266071China School of Control Science and Engineering Shandong UniversityJinan 250061China

In this paper,the strong structural controllability of the leader-follower framework is ***,the authors analyze different edge augmentation methods to preserve the strong structural controllability of the path-bud *** following four cases are considered:Adding edges from the path to the bud;adding edges from the bud to the path;adding the reverse or forward edges to the path or bud;and adding both the reverse and forward edges to the path or *** sufficient conditions are derived for the strong structural controllability of the new topologies which are generated by adding different *** addition,it is proved that rank[A B]=n is a necessary condition for the strong structural ***,three examples are given to verify the effectiveness of the main results.

关键词： Edge augmentation leader-follower framework path-bud topology strong structural controllability

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A Dynamic Gain Method to Event-Triggered Tracking control for Uncertain Nonlinear Systems With Input Quantization

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IEEE Transactions on Automatic control 2025年第6期70卷 4093-4100页

作者： Li, Hanfeng Li, Min Shandong University School of Control Science and Engineering Shandong Jinan250061 China Shandong University Institute of Geotechnical and Underground Engineering Shandong Jinan250061 China

This paper proposes a dynamic gain method to solve the event-triggered output feedback tracking control problem of uncertain strict- feedback nonlinear systems subject to input quantization. The nonlinear terms admit an incremental rate depending on an unknown constant and an output polynomial function. Two configurations of the event-triggered quantized controller are presented, namely quantization after triggering and quantization before triggering. Based on the dynamic scaling transformations, the continuous controllers are designed respectively for these two configurations. By introducing the novel quantizers and threshold strategies, the desired discrete controllers are obtained. For both of the configurations, the tracking error converges within the pre-specified small interval. Moreover, all the closed-loop signals are bounded and the Zeno phenomenon is avoided. In contrast to many existing results on tracking control of nonlinear systems, the proposed dynamic gain method is more concise and liable to implement. A simulation example is provided to verify the effectiveness of the proposed control schemes. © 1963-2012 IEEE.

关键词： Nonlinear feedback

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Drug-Target Interactions Prediction Based on Signed Heterogeneous Graph Neural Networks

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Chinese Journal of Electronics 2024年第1期33卷 231-244页

作者： Ming CHEN Yajian JIANG Xiujuan LEI Yi PAN Chunyan JI Wei JIANG College of Information Science and Engineering Hunan Normal University School of Computer Science Shaanxi Normal University Faculty of Computer Science and Control Engineering Shenzhen Institute of Advanced TechnologyChinese Academy of Sciences Computer Science Department BNU-HKBU United International College

Drug-target interactions(DTIs) prediction plays an important role in the process of drug *** computational methods treat it as a binary prediction problem, determining whether there are connections between drugs and targets while ignoring relational types information. Considering the positive or negative effects of DTIs will facilitate the study on comprehensive mechanisms of multiple drugs on a common target, in this work, we model DTIs on signed heterogeneous networks, through categorizing interaction patterns of DTIs and additionally extracting interactions within drug pairs and target protein pairs. We propose signed heterogeneous graph neural networks(SHGNNs), further put forward an end-to-end framework for signed DTIs prediction, called SHGNN-DTI,which not only adapts to signed bipartite networks, but also could naturally incorporate auxiliary information from drug-drug interactions(DDIs) and protein-protein interactions(PPIs). For the framework, we solve the message passing and aggregation problem on signed DTI networks, and consider different training modes on the whole networks consisting of DTIs, DDIs and PPIs. Experiments are conducted on two datasets extracted from Drug Bank and related databases, under different settings of initial inputs, embedding dimensions and training modes. The prediction results show excellent performance in terms of metric indicators, and the feasibility is further verified by the case study with two drugs on breast cancer.

关键词： Drug-target interactions Signed heterogeneous network Link sign prediction Graph neural networks

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Investigating the Logical Capability of Graph Neural Networks via the Connection to C_(2)

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Data Intelligence 2024年第3期6卷 720-748页

作者： Zhangquan Zhou Shijiao Tang School of Command and Control Engineering Army Engineering University of PLA Nanjing 210001China School of Information Science and Engineering Nanjing Audit University Jinshen College Nanjing 210023China

Graph neural networks(GNNs)have garnered substantial application across a spectrum of real-world scenarios due to their remarkable ability to handle data organized in the form of ***,the full extent of GNNs'computational properties and logical capability remains a subject of ongoing *** study undertakes an exploration of the logical capabilities intrinsic to GNNs,approaching the matter from a theoretical *** this pursuit,a pivotal connection is established between GNNs and a specific fragment of first-order logic known as C_(2),which serves as a logical framework for modeling graph *** research further amplifies this discourse,introducing a subcategory of GNNs named ACR-GNN,illustrating that GNNs are capable of emulating the evaluation process of unary C,*** on these insights,we introduce an innovative version of GNN architectures capable of dealing with general C,*** attain this,we employ a mechanism known as message passing for GNN *** proposed GNN adaptations allow for simultaneous updating of node and node pair features,thereby enabling the management of both unary and binary C,*** prove that the proposed models exhibit the equivalent expressiveness to C_(2).This underpins the profound alignment between the logical capability of GNNs and the inherent nature of the logical language C,.We conduct several experiments on both of synthetic and real-world datasets to support our *** the experiments,we verify that our suggested models outperform both ACR-GNN and a commonly used model,GIN,when it comes to evaluating C,formulas.

关键词： Graph neural networks Logical capabilities C_(2)logical language

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Digital Twin Virtual-Real Synchronization for Aeroengine Gas Path System Based on Deep Reinforcement Learning

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IEEE Systems Journal 2025年第1期19卷 75-86页

作者： Xu, Changyi Huo, Yuming Shi, Chunkun Zhao, Ying Dalian University of Technology School of Control Science and Engineering Dalian116023 China Dalian Maritime University College of Marine Electrical Engineering Dalian116026 China

It is crucial to monitor the operational status of aeroengines by using the digital twin technology to realize virtual-real synchronization for the gas path system. The challenge is to accurately monitor deep parameters in real-time during synchronization, although existing digital twin technologies have made good progress in monitoring shallow parameters. This study proposes a virtual-real synchronization method for digital twins of an aeroengine gas path system (AGPS) based on deep reinforcement learning (RL). First, the parameters are divided into directly measurable parameters (DMP) and nondirectly measurable parameters (NDMP). Then, different algorithms are applied to different types of parameters. An unscented Kalman filtering algorithm is utilized to aid in the synchronization of the DMP. An RL approach is employed to train parameter inference models for the NDMP. By combining the two algorithms, synchronization between these two parameter classes is achieved. This method excels by integrating the NDMP into the virtual-real synchronization of the AGPS digital twin, concurrently reducing the inference time for this specific segment. Comparative experiments are conducted, and the results indicate an effective improvement in the accuracy of parameter inference with the proposed method. Simultaneously, it ensures real-time and robust parameter inference. © 2007-2012 IEEE.

关键词： Deep reinforcement learning

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Preparation and photocatalytic performance study of dual Z-scheme Bi_(2)Zr_(2)O_(7)/g-C_(3)N4/Ag_(3)PO_(4) for removal of antibiotics by visible-light

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Journal of Environmental sciences 2023年第3期125卷 349-361页

作者： Zhengjun Qu Zhenyang Jing Xiaoming Chen Zexiang Wang Hongfei Ren Lihui Huang Shandong Key Laboratory of Water Pollution Control and Resource Reuse School of Environmental Science and EngineeringShandong UniversityQingdao 266237China

At present,the high re-combination rate of photogenerated carriers and the low redox capability of the photocatalyst are two factors that severely limit the improvement of photocatalytic ***,a dual Z-scheme photocatalyst bismuthzirconate/graphitic carbon nitride/silver phosphate (Bi_(2)Zr_(2)O_(7)/g-C_(3)N4/Ag_(3)PO_(4)(BCA)) was synthesized using a co-precipitation method,and a dual Z-scheme heterojunction photocatalytic system was established to decrease the high re-combination rate of photogenerated carriers and consequently improve the photocatalytic *** re-combination of electron-hole pairs(e-and h+) in the valence band (VB) of g-C_(3)N4increases the redox potential of e-and h+,leading to significant improvements in the redox capability of the photocatalyst and the efficiency of e--h+*** a photosensitizer,Ag_(3)PO_(4)can enhance the visible light absorption capacity of the *** prepared photocatalyst showed strong stability,which was attributed to the efficient suppression of photo-corrosion of Ag_(3)PO_(4)by transferring the e-to the VB of g-C_(3)*** was degraded efficiently by BCA-10%(the BCA with 10 wt.%of AgPO_(4)) under visible light,and the degradation efficiency was up to 86.2%.This study experimentally suggested that the BCA photocatalyst has broad application prospects in removing antibiotic pollution.

关键词： Photocatalysis Bi_(2)Zr_(2)O_(7)/g-C_(3)N4/Ag_(3)PO_(4) Dual Z-scheme photocatalytic system Visible light Tetracycline

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