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GCARDTI:Drug–target interaction prediction based on a hybrid mechanism in drug SELFIES

Quantitative Biology 2024年第2期12卷 141-154页

作者： Yinfei Feng Yuanyuan Zhang Zengqian Deng Mimi Xiong School of Information and Control Engineering Qingdao University of TechnologyQingdaoChina Qingdao Municipal Hospital QingdaoChina

The prediction of the interaction between a drug and a target is the most critical issue in the fields of drug development and ***,there are still two challenges in current deep learning research:(i)the structural information of drug molecules is not fully explored in most drug target studies,and the previous drug SMILES does not correspond well to effective drug molecules and(ii)exploration of the potential relationship between drugs and targets is in need of *** this work,we use a new and better representation of the effective molecular graph structure,*** propose a hybrid mechanism framework based on convolutional neural network and graph attention network to capture multi-view feature information of drug and target molecular structures,and we aim to enhance the ability to capture interaction sites between a drug and a *** this study,our experiments using two different datasets show that the GCARDTI model outperforms a variety of different model algorithms on different *** also demonstrate the accuracy of our model through two case studies.

关键词： drug–target interaction drug SELFIES hybrid mechanism random forest

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Data Driven Comprehensive Performance Evaluation of Aeroengines:A Network Dynamic Approach

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engineering 2025年第3期46卷 292-305页

作者： Yuting Wang Feng Liu Feng Xi Bofei Wei Dongli Duan Zhiqiang Cai Shubin Si School of Mechanical Engineering Northwestern Polytechnical UniversityXi’an 710072China Key Laboratory of Industrial Engineering and Intelligent Manufacturing(Ministry of Industry and Information Technology of the People’s Republic of China) Xi’an 710072China AECC Aviation Power Co. Ltd.Xi’an 710005China School of Information and Control Engineering Xi’an University of Architecture and TechnologyXi’an 710311China

Aeroengines,often regarded as the heart of aircraft,are crucial for flight safety and *** performance evaluation of aeroengines supports Prognostics and Health Management(PHM)and aeroengine digital *** to their highly integrated nature,aeroengines present challenges in performance evaluation because their test-run data are high-dimensional,large-scale,and exhibit strong nonlinear correlations among test *** solve this problem,this study proposes a unified framework of the comprehensive performance evaluation of aeroengines to assess performance objectively and ***,the network model and the dynamics model of aeroengine performance are constructed driven by test-run data,which can explain the patterns of system state changes and the internal relationship,and depict the system *** on that,three perturbations in the model are used to simulate three fault modes of ***,the comprehensive performance evaluation indexes of aeroengines are proposed to evaluate the performance dynamically from two dimensions,the coupling performance and the activity *** test-run qualified and four test-run failed aeroengines are used to validate and establish the qualified *** results demonstrate that the comprehensive evaluation indexes can distinguish test-run qualified and test-run failed *** changing the dynamic parameters,the comprehensive performance under any thrust and inlet guide vanes(IGV)angle can be estimated,broadening the test-run scenarios beyond a few typical *** novel approach offers significant advancements for the comprehensive performance evaluation and management of aeroengines,paving the way for future PHM and aeroengine digital engineering developments.

关键词： Comprehensive performance evaluation Aeroengine performance Network Resilience

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Machine learning based damage state identification:A novel perspective on fragility analysis for nuclear power plants considering structural uncertainties

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Earthquake engineering and engineering Vibration 2025年第1期24卷 201-222页

作者： Zheng Zhi Wang Yong Pan Xiaolan Ji Duofa College of Civil Engineering Taiyuan University of TechnologyTaiyuan 030024China Key Lab of Structures Dynamic Behavior and Control(Harbin Institute of Technology) Ministry of EducationHarbin 150090China Key Lab of Smart Prevention and Mitigation of Civil Engineering Disasters of the Ministry of Industry and Information Technology Harbin Institute of TechnologyHarbin 150090China

Seismic fragility analysis(SFA)is known as an effective probabilistic-based approach used to evaluate seismic *** are various sources of uncertainties associated with this approach.A nuclear power plant(NPP)system is an extremely important infrastructure and contains many structural uncertainties due to construction issues or structural deterioration during *** of structural uncertainties effects is a costly and time-consuming endeavor.A novel approach to SFA for the NPP considering structural uncertainties based on the damage state is proposed and *** results suggest that considering the structural uncertainties is essential in assessing the fragility of the NPP structure,and the impact of structural uncertainties tends to increase with the state of ***,machine learning(ML)is found to be superior in high-precision damage state identification of the NPP for reducing the time of nonlinear time-history analysis(NLTHA)and could be applied in the damage state-based ***,the impact of various sources of uncertainties is investigated through sensitivity *** Sobol and Shapley additive explanations(SHAP)method can be complementary to each other and able to solve the problem of quantifying seismic and structural uncertainties simultaneously and the interaction effect of each parameter.

关键词： seismic fragility analysis damage state structural uncertainties machine learning sensitivity analysis

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Study on Dry Electrical Discharge Assisted Grinding of SiCp/Al Composite

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Chinese Journal of Mechanical engineering 2025年第1期38卷 106-118页

作者： Yanjun Lu Yuming Huang Xiaobu Liu Rong Cheng Shunda Zhan Guangdong Provincial Key Laboratory of Micro/Nano Optomechatronics Engineering College of Mechatronics and Control EngineeringShenzhen UniversityShenzhen 518060China School of Intelligent Manufacturing and Equipment Shenzhen Institute of Information TechnologyShenzhen 518172China

SiC-reinforced aluminum matrix(SiCp/Al)composite is widely utilized in the aerospace,automotive,and electronics industries due to the combination of ceramic hardness and metal ***,the significant disparity in properties between SiC particles and the aluminum matrix results in severe tool wear and diminished surface quality during conventional *** study proposes an environmentally friendly and clean dry electrical discharge assisted grinding process as an efficient and low-damage machining method for SiCp/*** experimental platform was set up to study the impact of grinding and discharge process parameters on surface *** study compared the chip formation mechanism and surface quality between dry electrical discharge assisted grinding and conventional grinding,revealing relationships between surface roughness,grinding force,grinding temperature,and related *** results indicate that the proposed grinding method leads to smaller chip sizes,lower grinding forces and temperatures,and an average reduction of 19.2%in surface roughness compared to conventional *** axial,tangential,and normal grinding forces were reduced by roughly 10.5%,37.8%,and 23.0%,*** optimized process parameters were determined to be N=2500 r/min,vf=30 mm/min,a=10μm,E=15 V,f=5000 Hz,dc=80%,resulting in a surface roughness of 0.161μm.

关键词： Dry electrical discharge assisted grinding SiCp/Al composite Surface quality Grinding force Grinding temperature

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Hybrid Optimization Algorithm for Handwritten Document Enhancement

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Computers, Materials & Continua 2024年第3期78卷 3763-3786页

作者： Shu-Chuan Chu Xiaomeng Yang Li Zhang Václav Snášel Jeng-Shyang Pan College of Computer Science and Engineering Shandong University of Science and TechnologyQingdao266590China School of Information and Control Engineering Qingdao University of TechnologyQingdao266520China Faculty of Electrical Engineering and Computer Science VŠB-TU OstravaOstrava70080Czech Republic Department of Information Management Chaoyang University of TechnologyTaichung41349Taiwan

The Gannet Optimization Algorithm (GOA) and the Whale Optimization Algorithm (WOA) demonstrate strong performance;however, there remains room for improvement in convergence and practical applications. This study introduces a hybrid optimization algorithm, named the adaptive inertia weight whale optimization algorithm and gannet optimization algorithm (AIWGOA), which addresses challenges in enhancing handwritten documents. The hybrid strategy integrates the strengths of both algorithms, significantly enhancing their capabilities, whereas the adaptive parameter strategy mitigates the need for manual parameter setting. By amalgamating the hybrid strategy and parameter-adaptive approach, the Gannet Optimization Algorithm was refined to yield the AIWGOA. Through a performance analysis of the CEC2013 benchmark, the AIWGOA demonstrates notable advantages across various metrics. Subsequently, an evaluation index was employed to assess the enhanced handwritten documents and images, affirming the superior practical application of the AIWGOA compared with other algorithms.

关键词： Metaheuristic algorithm gannet optimization algorithm hybrid algorithm handwritten document enhancement

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Dynamic event-triggered consensus control for nonlinear multi-agent systems under DoS attacks

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Mathematical Biosciences and engineering 2024年第2期21卷 3304-3318页

作者： Wang, Qiushi Ren, Hongwei Peng, Zhiping Huang, Junlin School of Automation Guangdong University of Petrochemical Technology Maoming525000 China School of Information and Control Engineering Jilin Institute of Chemical Technology Jilin132000 China

In this paper, we investigated leader-following consensus control for nonlinear multiagent systems (MASs) experiencing denial-of-service (DoS) attacks. We proposed a distributed control strategy incorporating an adaptive scheme and a state feedback control gain to eliminate the effects of system nonlinear dynamics and uncertainties. In addition, we introduced a dynamic event-triggered control (DETC) to minimize the utilization of communication resources. Finally, we provided simulation results to show the validity of the proposed approach. © 2024 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License.

关键词： Multi agent systems

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An Enhanced Robustness Dual-Vector Model Predictive Torque control for Permanent Magnet Synchronous Motors

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Progress In Electromagnetics Research C 2024年 140卷 53-64页

作者： Xie, Hao Zhang, Cheng Zhang, Yang Li, Sicheng College of Electrical and Information Engineering Hunan University of Technology Zhuzhou412007 China Railway Traffic Control Technology Co. Ltd Changsha410000 China

The traditional dual-vector model predictive torque control (MPTC) of permanent magnet synchronous motor suffers from the problems of large control computation, large torque ripple, and prediction deviation due to parameter mismatch. To address these issues, an enhanced robustness dual-vector MPTC (ERD-MPTC) control strategy is proposed in this paper. First, in order to reduce the control computation, a fast voltage vector selection table based on a 12-sector voltage vector map is proposed, which reduces the number of prediction iterations from 14 to only 3. Secondly, to reduce the ripple of torque and flux in one cycle, the cost function without weight factor is proposed. This cost function includes fluctuations at the moment of the switching point. Then, for the bad effects of parameter mismatch, the inductance parameter is estimated by using the amount of error variation between the predicted value and the actual measured value at adjacent moments. So, an ERD-MPTC strategy to enhance the robustness of the prediction model in the presence of parameter mismatch is proposed by integrating the inductance updating mechanism and expanded state observer. Finally, through the experiment, it is shown that the proposed strategy can reduce the torque fluctuation, effectively reduce the adverse effects of parameter changes, and greatly improve the stability of the system. © 2024, Electromagnetics Academy. All rights reserved.

关键词： Inductance

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Algorithmic Decomposition of Railway Objects for Distributed Interlocking System

Periodica Polytechnica Electrical Engineering and Computer S...

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Periodica Polytechnica Electrical engineering and Computer Science 2024年第4期68卷 319-326页

作者： Arató, Péter Markovits, Tibor Gergely Rácz, György Department of Control Engineering and Information Technology Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics Magyar tudósok krt. 2. BudapestH-1117 Hungary

Railway interlocking systems can be implemented as distributed systems, where each part of a station is handled by a separate logical unit. The logical units of such systems form a network and communicate by interchanging messages. Such distributed architectures are well known in large industrial control systems. There are several design practices and also algorithmic task partitioning methods that are applicable in distributed control systems. Some of such methods can also be adapted in designing of railway interlocking systems as well. In the case of such systems, the communication time between components must be kept low. Namely each separate controller in a given route must be able to exchange their internal state within a limited time in order to permit the train movement authorization. This limitation could cause high traffic load, if every logical unit would be interconnected with each other. Therefore, the main goal of the minimization is to reduce the number of connections between logical units. This can achieved by distributing and assigning the topological railway objects to certain logical units. © 2024 Budapest University of technology and Economics. All rights reserved.

关键词： Distributed parameter control systems

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MAO-DBN based membrane fouling prediction

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Journal of Intelligent and Fuzzy Systems 2024年第4期46卷 10923-10939页

作者： Wang, Zhiwen Zhao, Yibin Shi, Yaoke Ling, Guobi College of Electrical and Information Engineering Lanzhou University of Technology Lanzhou China Key Laboratory of Gansu Advanced Control for Industrial Processes Lanzhou University of Technology Lanzhou China National Demonstration Center for Experimental Electrical and Control Engineering Education Lanzhou University of Technology Lanzhou China

Due to the complexity of the factors influencing membrane fouling in membrane bioreactors (MBR), it is difficult to accurately predict membrane fouling. This paper proposes a multi-strategy of integration aquila optimizer deep belief network (MAO-DBN) based membrane fouling prediction method. The method is developed to improve the accuracy and efficiency of membrane fouling prediction. Firstly, partial least squares (PLS) are used to reduce the dimensionality of many membrane fouling factors to improve the algorithm's generalization ability. Secondly, considering the drawbacks of deep belief network (DBN) such as long training time and easy overfitting, piecewise mapping is introduced in aquila optimizer (AO) to improve the uniformity of population distribution, while adaptive weighting is used to improve the convergence speed and prevent falling into local optimum. Finally, the prediction of membrane fouling is carried out by utilizing membrane fouling data as the research object. The experimental results show that the method proposed in this paper can achieve accurate prediction of membrane fluxes, with an 88.45% reduction in RMSE and 87.53% reduction in MAE compared with the DBN model before improvement. The experimental results show that the model proposed in this paper achieves a prediction accuracy of 98.61%, both higher than other comparative models, which can provide a theoretical basis for membrane fouling prediction in the practical operation of membrane water treatment. © 2024-IOS Press. All rights reserved.

关键词： Bioreactors

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Robust Trajectory Tracking control of a Differentially Flat Overhead Crane Using Sliding Mode

Periodica polytechnica Electrical engineering and computer s...

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Periodica polytechnica Electrical engineering and computer science 2024年第2期68卷 213-221页

作者： Finta, Barnabás Kiss, Bálint Department of Control Engineering and Information Technology Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics University Műegyetem rkp. 3. BudapestH-1111 Hungary

The control of overhead cranes is a benchmark problem, since it is an underactuated mechanism and its mathematical model is nonlinear. During operation the mass of the load is unknown, representing an uncertainty in the inertial parameters, which requires robustness of the controlled system. Our paper proposes a novel robust control method, that combines the differentially flat property of the dynamics with the robustness of the sliding mode control. The sliding surface is constructed to ensure the tracking of the configuration variables whose accelerations is calculated using the flatness property of the dynamic model. This formulation also allows achieving the matching conditions of the parameter uncertainties. Considering a simplified overhead crane model where the load motion is restricted in a vertical plane, two sliding surfaces are defined for the rope angle and rope length, since the cart position can be calculated from the previous two. The suggested control method is successfully validated in simulations as well as using a reduced-size overhead crane. For the real crane, the rope angle was estimated by utilizing the dynamical model, which uses the estimated cart acceleration. © 2024 Budapest University of technology and Economics. All rights reserved.

关键词： Acceleration

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