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10th China Health Information Processing Conference, CHIP 2024

作者： Zhao, Haixue Yao, Kui Liu, Yunjiong Che, Chao Tang, Lin Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education Dalian University Dalian116622 China School of Software Engineering Dalian University Dalian116622 China

ISBN: (纸本)9789819637515

Drug-target interaction prediction help reduce the cost and time of drug development. However, existing research often overlooks the complexity of biological interactions. To address this issue, this paper proposes a DTI prediction model that integrates multi-dimensional biochemical features. Specifically, the model utilizes a heterogeneous graph attention network to capture the topological relationships among biological entities from diverse data, providing a deep understanding of the interactions among drugs, proteins, diseases, and side effects. A molecular attention Transformer network and a CBiNet module are used to extract the key structural features of drugs and targets. By automatically optimizing the weight distribution between drugs and targets, the model enhances the information transfer during network training, significantly improving model performance. Experimental results on real-world datasets demonstrate that the proposed model outperforms the current state-of-the-art methods in the field. Among the top 50 novel COVID-19 therapeutic drugs predicted by our model, 30 have been supported by clinical trials or scientific literature, further demonstrating the effectiveness of our proposed method in drug repurposing. Experimental data and supplementary materials are available online at: https://***/Eadog/MBF-DTI. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： COVID-19

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Deep Reinforcement Learning with Human Guidance for Autonomous Driving Car Following

Deep Reinforcement Learning with Human Guidance for Autonomo...

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IEEE International Conference on Mechatronics, Robotics and Automation (ICMRA)

作者： Wenbo Wang Qingchao Xu Xingfu Yang Yandong Liu School of Software Engineering Dalian University Dalian China Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education Dalian University Dalian China

ISBN: (数字)9798350307535

ISBN: (纸本)9798350307542

To solve the complex modeling and difficult parameter adjustment of traditional car-following control methods, we propose the car-following framework KgPPO-CF. The KgPPOCF brings expert experience into the interactive process of Deep Reinforcement Learning, which improves the speed and robustness of training policies. We use four different reward functions and compare the effects of policies trained by different designs on car-following control. In the Carla simulator, KgPPO-CF achieves car-following control in a continuous action space. The experimental results show that, compared with the traditional control methods, the control strategy obtained by KgPPO-CF training has better adaptability.

关键词： Training Accuracy Mechatronics Aerospace electronics Deep reinforcement learning Robustness Automobiles Robotics and automation Standards Autonomous vehicles

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Finite-Time Synchronization of Flux-Controlled Complex-Valued Memristive Neural Networks

Finite-Time Synchronization of Flux-Controlled Complex-Value...

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2023 International Conference on Neuromorphic computing, ICNC 2023

作者： Wang, Yonghuan Wang, Leimin Wu, Genping China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education School of Automation Wuhan430074 China Wuhan Second Ship Design and Research Institute Wuhan430064 China

ISBN: (纸本)9798350316889

In this paper, by using the flux-controlled memristor model, the finite-time synchronization problem of delayed complex-valued memristive neural networks (MCNNs) is studied. Firstly, according to the proposed memristor model, we model the MCNNs as continuous systems on voltage-flux-time (wp, varpi, t) domain. Then, we design a class of approaches to realize state synchronization between the drive and response systems, and the corresponding synchronization conditions are achieved. Finally, the effectiveness of results is illustrated with the simulations. © 2023 IEEE.

关键词： Memristors

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MFN: Explainable DNA triple helixes Stabilized design based on mCGR and flow network

MFN: Explainable DNA triple helixes Stabilized Design based ...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Xiaoru Wen Lijun Sun Lei Xie Yanfen Zheng Ben Cao Bin Wang Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education School of Software Engineering Dalian University Dalian China School of Computer Science and Technology Dalian University of Technology Dalian China

ISBN: (数字)9798350386226

ISBN: (纸本)9798350386233

DNA triple helix structure, as a highly specific gene targeting tool, enable gene regulation by precisely identifying and binding to target DNA sequences. However, the limits of design quality and efficiency affect their wide application in gene therapy. Therefore, in this paper, we propose an antiparallel DNA triple helixes design method-MFN based on matrix chaotic game representation (mCGR) and flow network. Leveraging the structural characteristics of DNA sequences, this method employs the mCGR algorithm to construct an initial matrix, generating a set of DNA sequences that conform to foundational constraints. Then, these sequences are mapped as stream network nodes to screen crosstalk structures by path search, and the whole process is observable and interpretable. Experimental results show that MFN significantly improves the design efficiency of triple helix structure and reduces crosstalk phenomenon. Wet experiments further verify the effectiveness of the method. In summary, MFN achieves an efficient and high-quality design of DNA triple helixes and provides a new idea for targeted gene therapy.

关键词： Scalability design methodology DNA Crosstalk Genomics Games Reliability engineering Regulation Gene therapy Bioinformatics

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Positive-Unlabeled Learning with Field of View Consistency for Histology Image Segmentation 1

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13th International Conference on Frontier computing, FC 2023

作者： Jia, Xiaoqi Fu, Chong Hou, Jiaxin Qin, Wenjian School of Computer Science and Engineering Northeastern University Shenyang110819 China Key Laboratory of Intelligent Computing in Medical Image Ministry of Education Northeastern University Shenyang110819 China Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China Shenzhen College of Advanced Technology University of Chinese Academy of Sciences Shenzhen518055 China

ISBN: (数字)9789819993420

ISBN: (纸本)9789819993413

Histology image annotation is costly and time-consuming. Utilizing Positive and Unlabeled (PU) data for model training offers a more resource-efficient alternative. However, previous methods for PU learning suffer from the noise arising from label assignment to unlabeled data. We observe that predictions on noisy data lack consistency under data augmentation. In this paper, we present Field of View (FoV) consistency regularization for PU segmentation in histology images, which effectively reduces the noise influence by promoting consistent predictions across varying FoVs. Using only 20% of positive labels on the Glas Dataset, our approach outperforms previous methods, achieving a Dice score of 90.69%-almost reaching the fully supervised result of 93.30%. Source code is available at: https://***/lzaya/PU_with_FoV. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2024.

关键词： Image segmentation

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Compactness and Separateness Driven Fuzzy Clustering Validity Index Called TLW 18th

Compactness and Separateness Driven Fuzzy Clustering Validit...

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18th CCF Conference on Computer Supported Cooperative Work and Social computing, ChineseCSCW 2023

作者： Tang, Yiming Wang, Xiang Li, Bing Hu, Xianghui Xie, Wenjun Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine School of Computer and Information Hefei University of Technology Anhui Hefei230601 China Engineering Research Center of Safety Critical Industry Measure and Control Technology Ministry of Education Hefei University of Technology Anhui Hefei230601 China

ISBN: (纸本)9789819996391

The design of validity index of fuzzy clustering has always been a historical problem in fuzzy clustering field. When the distribution of cluster centers is very close, it is difficult for the existing fuzzy clustering validity indexes to obtain a reasonable cluster number, and the separation mechanism of these indexes is too simple. In order to solve the above problems, we propose a novel fuzzy clustering validity index called TLW (Tang-Li-Wang) index. Firstly, compactness is expressed as the ratio of the membership weighted distance value to the sample variance of the dataset. Secondly, the sum of the maximum distance between cluster centers and the mean distance is used in separateness, and the sample variance of cluster centers is introduced, and the two are multiplied to describe the separateness. Thirdly, on the basis of considering compactness and separateness, the introduction of cluster number can alleviate the phenomenon that the index value may change monotonically with the increase of cluster number. Finally, the classical FCM (Fuzzy C-Mean) algorithm is used to conduct experiments on indexes. Comparative experiments and analyses were carried out on 17 typical datasets and 12 clustering validity indexes. From the experimental results of normal simple datasets and high-dimensional difficult datasets, the proposed index shows some advantages. All in all, these results verify that the proposed TLW index has better accuracy and stronger stability. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Fuzzy clustering

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Nonreciprocity of energy transfer in a nonlinear asymmetric oscillator system with various vibration states

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Applied Mathematics and Mechanics(English Edition) 2023年第5期44卷 727-744页

作者： Jian’en CHEN Jianling LI Minghui YAO Jun LIU Jianhua ZHANG Min SUN Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical EngineeringTianjin University of TechnologyTianjin 300384China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin University of TechnologyTianjin 300384China School of Aeronautics and Astronautics Tiangong UniversityTianjin 300387China Agricultural Information Institute of Chinese Academy of Agricultural Sciences Key Laboratory of Agricultural Big DataMinistry of Agriculture and Rural AffairsBeijing 100081China School of Science Tianjin Chengjian UniversityTianjin 300384China

The nonreciprocity of energy transfer is constructed in a nonlinear asymmetric oscillator system that comprises two nonlinear oscillators with different parameters placed between two identical linear *** slow-flow equation of the system is derived by the complexification-averaging *** semi-analytical solutions to this equation are obtained by the least squares method,which are compared with the numerical solutions obtained by the Runge-Kutta *** distribution of the average energy in the system is studied under periodic and chaotic vibration states,and the energy transfer along two opposite directions is *** effect of the excitation amplitude on the nonreciprocity of the system producing the periodic responses is analyzed,where a three-stage energy transfer phenomenon is *** the first stage,the energy transfer along the two opposite directions is approximately equal,whereas in the second stage,the asymmetric energy transfer is *** energy transfer is also asymmetric in the third stage,but the direction is reversed compared with the second ***,the excitation amplitude for exciting the bifurcation also shows an asymmetric *** vibrations are generated around the resonant frequency,irrespective of which linear oscillator is *** excitation threshold of these chaotic vibrations is dependent on the linear oscillator that is being *** addition,the difference between the energy transfer in the two opposite directions is used to further analyze the nonreciprocity in the *** results show that the nonreciprocity significantly depends on the excitation frequency and the excitation amplitude.

关键词： nonreciprocity strong nonlinearity energy transfer chaotic vibration higher branch of response

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Performance Verification of State Feedback H∞ State Molecular Controller Via Chemical Reaction Networks 5

Performance Verification of State Feedback H∞ State Molecul...

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5th International Conference on Industrial Artificial Intelligence, IAI 2023

作者： Yao, Jingwang Wang, Xing'An Lv, Hui Li, Yang Zhang, Wujie Dalian University Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education School of Software Engineering Dalian116622 China Dalian University College of Environmental and Chemical Engineering Dalian116622 China Dalian Chivy Biotechnology Co. Ltd Dalian116023 China Northeastern University State Key Laboratory of Synthetical Automation for Process Industries Shenyang110004 China

ISBN: (纸本)9798350325294

An important goal in synthetic biology is in the design and implementation of control strategies embedded in biochemical reaction systems to enable control of the process at the molecular level. The problem of set-point tracking and perturbation disturbances in the biochemical reaction process can be solved by a state feedback control strategy and a more stable and better dynamic performance of synthetic controllers. First, it is shown how a set of CRNs can provide state feedback to the biomolecular implementation of the H∞ controller. Then, to facilitate the modularity of biochemical process design, CRNs of trigonometric functions and repetitive sequence step signals are defined for the first time as input signals to the controller. Finally, numerical simulation experiments are designed to verify the effectiveness of the whole scheme from several perspectives, such as setpoint tracking and external perturbations. The results show that the state feedback H∞ molecular controller outperforms the conventional linear controller because it has a faster tracking response and better perturbation rejection performance. © 2023 IEEE.

关键词： Controllers

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Rsta: A Reversible Signal Transmission Architecture for Breaking the Limitation of Unidirectional Transmission

SSRN

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SSRN 2025年

作者： Liu, Xin Cui, Shuang Zhang, Xun Zhou, Fuxing Sheng, Kaikai Wang, Bin Zhang, Qiang School of Computer Science and Technology Dalian University of Technology Dalian116024 China Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education School of Software Engineering Dalian University Dalian116622 China

Molecular circuits are essential tools for biosensing and molecular information processing. However, the long-distance and reversible transmission of orthogonal signals remains a significant challenge in molecular circuits, preventing molecular signals from achieving reversible transmission similar to that of electrical signals in wires. To overcome the limitations of unidirectional signal transmission and facilitate the integration of antagonistic circuits. We propose a reversible signal transmission architecture (RSTA) with wire-like characteristics to achieve reversible signal transmission based on fundamental molecular devices known as reversible signal fan-out devices (RSFDs). The polarity of the input signal dictates the transmission direction, establishing the initial condition for the output signals. Cascaded RSFDs within RSTA offer two key advantages. First, the temporal response to signals. Second, the reversible transformation of opposite circuit types without structural modification. We experimentally validated the principles and functionality of RSTA using temporal logic device and integrated molecular circuits. This work advances the field of reversible molecular signal transmission, enabling the rational design of complex molecular circuits and molecular information processing systems. We envision applications of this technology in nanomachines, molecular computing, and biosensing. © 2025, The Authors. All rights reserved.

关键词： Temporal logic

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keyword mask pre-training model for the review of standard declaration

Keyword mask pre-training model for the review of standard d...

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International Conference on Computer Engineering and Applications (ICCEA)

作者： Chuang Feng Chao Che Qiang Zhang Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education Dalian University Dalian China School of Computer Science and Technology Dalian University of Technology Dalian China

The review of standard declaration of import and export commodities refers to the evaluation of whether the declaration information of the commodities filled in by enterprises conforms to the customs filling standards according to the standardized declaration catalogue The manual review method cannot meet the actual work needs. Therefore, using text classification algorithm to conduct this task is necessary. The classification method based on the pre-training model would rely on the keywords. However, for the review of standard declaration task, excessive reliance on keywords will reduce the classification effect because of ignoring the overall information of the text. keyword mask pre-training model is proposed. In the fine-tuning stage, the model designs a keyword masking strategy and a keyword blinding strategy. The keyword masking strategy regularizes the BERT model with a mask mechanism, that is, the keywords are reconstructed with other text information except keywords, so that the model focuses on non-keywords information; keyword blinding strategy makes the model unable to distinguish the categories of text information without contextual text information, which can eliminate the influence of keywords on model decision-making. The experimental results on the real customs declaration data set showing that the method in this thesis exceeds the baseline method in terms of precision and true negative rate.

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